Performance Evaluation of the Physical Layer of IEEE 802.16e standard
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Transcript of Performance Evaluation of the Physical Layer of IEEE 802.16e standard
Performance Evaluation of the Physical Layer of IEEE 802.16e standard
A Dissertation
Submitted in partial fulfillment of the requirements for the award of the Degree of
MASTER OF TECHNOLOGY In INFORMATION & COMMUNICATION TECHNOLOGY
(Specialization in Wireless Communication & Networks)
Submitted by: VIPIN SHARMA
10-PIT-042
Supervisor: Mr. Sandeep Sharma
Faculty Associate School of ICT, GBU
SCHOOL OF INFORMATION & COMMUNICATION TECHNOLOGY GAUTAM BUDDHA UNIVERSITY
GREATER NOIDA-201308, UTTAR PRADESH, INDIA May, 2012
School of Information and Communication Technology Gautam Buddha University, Greater Noida
Candidate’s Declaration
I hereby certify that the dissertation work embodied in this dissertation report by the roll no. 10-
PIT-042 entitled “Performance Evaluation of the Physical Layer of IEEE 802.16e standard” in
partial fulfillment of the requirements for the award of the degree of M.Tech. in ICT
specialization in Wireless Communication & Networks submitted to the school of ICT, Gautam
Buddha University, Grater Noida is an authentic record of my own work carried out under the
super vision of Mr. Sandeep Sharma.
The matter presented in this work has not been submitted by me in any other
University/Institution for the award of any other degree or diploma.
Vipin Sharma
(10-PIT-042)
The information furnished above is correct to the best of my knowledge and belief.
Date: 12 .May.2012
Place: Gautam Budh Nagar
(Mr. Sandeep Sharma)
Faculty Associate
School of ICT
Gautam Buddha University
Gautam Budh Nagar-201308
iii
Acknowledgements
I would like to acknowledge many people who have help me during the entire time of
dissertation work and supported it in one or another way. First of all, my admiration and
thanks go to my former dean “Dr. Brahmjit Singh.”
I wish to express my gratefulness to my supervisor, Mr. Sandeep Sharma, for his
seasoned guidance. Without his effective suggestions my work could not be completed. I
am deeply indebted to my parents for their inspiration and ever-encouraging moral
support, which enabled me to pursue my studies, I also want to thanks all my friend who
was always appreciate my work.
iv
Abstract WiMAX is given by the Institute of Electrical and Electronic Engineers which is a
standard designated as 802.16d (for fixed wireless user) and 802.16e (for mobile wireless
application) to provide a worldwide interoperability for microwave access. WiMAX has
proved to be a superior technology for BWA (Broadband Wireless Access) that
theoretically covers approx 30 to 50 Km. Physical layer of the WiMAX is based on
OFDM, that is the transmission scheme that’s provide the high-speed data for the video
and multimedia stemming and is used by the variety of commercial broadband technique
systems including DSL, Wi-Fi, and Digital Video Broadcast-Handheld, besides WiMAX.
OFDM is a refined and efficient scheme for high data rate transmission in a non-line-of-
sight and multipath fading radio environment.
WiMAX supports an Adaptive modulation and coding schemes that allows changing the
scheme on a burst-by-burst basis, depending on the channel conditions. Using the channel
quality feedback indicator, the base station can provide the downlink channel quality with
feedback and for the uplink channel quality the base station can estimate the received
signal strength through mobile station. Due to the multipath fading temporal variation in
channel, an AMC technique is beneficial with OFDM that’s minimizing the multipath
effect. This technique consist variety of modulation and channel encoding schemes to
provide the QoS by instantaneously adapting channel SNR variation, that’s provide the
maximizing throughput and improving BER performance at all channel condition.
In this paper we are preparing a model of WiMAX, where we studied different
modulation technique with different coding rate using the MATLAB 7.9.0 (R2009b)
simulink. All the parameter is taken from ETSI & IEEE Standard.
v
Table of Contents
Acknowledgement…………………………………………………………………… iii
Abstract……………………………………………………………………………… iv
List of Figure………………………………………………………………………… viii
List of Table………………………………………………………………………… x
List of Abbreviation.................................................................................................... xi
1. Chapter One
Introduction to WiMAX
1.1. Introduction……………………………………………………………………. 2
1.2. Motivation………………………………………………………...................… 2
1.3. Problem Definition…………………………………………………………… 3
1.4. Methodology.................................................................................................... 3
1.5. Application........................................................................................................ 4
1.6. Thesis Contribution…………………………………………..……………… 5
1.7. Outline of the Thesis………………………………………….……………… 5
2. Chapter Two
Literature Survey
2.1. Introduction..............…………………………………………………………. 9
2.2. Open Challenges and key issue……………………………….....................… 9
2.3. Classification of Methods………………………………………..…………… 16
2.4. Summarry……………….........................……………………….…………… 17
3. Chapter Three
IEEE 802.16: Evolution and Architecture
3.1. WiMAX at a Glance…………………………………………….……………. 19
3.2. Evolution of IEEE Family……………………………………....................… 20
3.2.1. IEEE 802.16 2001................................................................................... 21
3.2.2. IEEE 802.16 a 2002............................................................................... 22
3.2.3. IEEE 802.16c 2003................................................................................. 22
3.2.4. IEEE 802.16 2004.................................................................................. 22
vi
3.2.5. IEEE 802.16e 2005................................................................................ 24
3.3. Technical Overview.....………………………………………..……………… 25
3.3.1. IEEE 802.16 Protocol Layer.................................................................. 25
3.3.2. MAC Layer............................................................................................ 26
3.3.3. PHY Layer............................................................................................. 29
3.4. Physical Layer Adaptation…………………………………………………… 33
4. Chapter Four
Transmitter
4.1. Physical Layer Model.....………………….............………………………….. 35
4.2. Transmitter............. ………………...………………………………………… 35
4.3. Data Source....................................................................................................... 36
4.4. Channel Encoding............................................................................................. 38
4.4.1. Randomization....................................................................................... 38
4.4.2. R-S Encoding......................................................................................... 39
4.4.3. Convolution Encoding............................................................................ 44
4.4.4. Puncturing Process................................................................................. 47
4.4.5. Interleaving............................................................................................ 47
4.5. IQ Mapper......................................................................................................... 49
4.6. Principle of OFDM Transmission..................................................................... 52
5. Chapter Five
Channel
5.1. Radio Channel................………………….............………………………….. 58
5.2. Channel Model..... …………………………………………………………… 59
6. Chapter Six
Receiver
6.1. OFDM De-Mapping......………………….............………………………….. 63
6.2. IQ De-Mapping.... …………………………………………………………… 64
6.3. Channel Decoding............................................................................................. 64
6.3.1. Deinterleaving........................................................................................ 65
6.3.2. Inserting Zero......................................................................................... 65
6.3.3. Viterbi Decoder....................................................................................... 66
vii
6.3.4. R-S decoder............................................................................................. 67
7. Chapter Seven
Result & Analysis
7.1. Performance Evaluation………………………………………………………. 70
7.2. Probability of Symbol Error.............................................................................. 83
7.3. Analysis............................................................................................................. 84
8. Chapter Eight
Conclusion & Future Work
8.1. Conclusion........................................................................................................ 86
8.2. Limitation of Work........................................................................................... 86
8.3. Future Work..................................................................................................... 86
References...................................................................................................................... 87
Appendix A……………………………………………………………..…...........,..... 93
Appendix B……………………………………………………………..…...........,..... 99
viii
List of Figures
Figure 1: Basic Communication System................................................................... 6
Figure 2: Possible Scenario for the development of WiMAX.................................. 20
Figure 3: WiMAX Protocol Stack............................................................................ 26
Figure 4: WiMAX Physical and MAC Layer Architecture...................................... 27
Figure 5: Convergence in wireless communication.................................................. 32
Figure 6: Purpose of Mac Layer in WiMAX .......................................................... 32
Figure 7: Adaptive Modulation Scheme................................................................... 33
Figure 8: Transmitter for the WiMAX system......................................................... 35
Figure 9: Physical Layer Scenario............................................................................ 36
Figure 10: Channel Encoding- Randomizer with Shift Register................................ 39
Figure 11: General process of Reed-Solomon Encoder.............................................. 41
Figure 12: Process of shortening and puncturing of the RS code............................... 42
Figure 13: simulink scenario of the Reed-Solomon encoder of WiMAX.................. 43
Figure 14: simulink implementation of Reed-Solomon encoder of WiMAX............ 44
Figure 15: block diagram of convolution encoder...................................................... 16
Figure 16: Convolutional encoder of binary rate 1/2................................................. 46
Figure 17: Convolutional encoder implementation in simulink................................. 46
Figure 18: BPSK, 4-QAM and 16-QAM constellation map....................................... 51
Figure 19: Rearrangement performed before realizing the IFFT operation............... 53
Figure 20: Delay from front symbol........................................................................... 54
Figure 21: Cyclic prefix insertion.............................................................................. 54
Figure 22: OFDM symbol with the cyclic prefix...................................................... 56
Figure 23: Generating the OFDM symbol using the IFFT......................................... 56
Figure 24: Signal Losses due to three Effects............................................................. 58
Figure 25: Simulink Implementation.......................................................................... 61
Figure 26: Block Diagram of Receiver...................................................................... 63
Figure 27: Block Diagram of channel Decoding........................................................ 65
Figure 28: Simulink implementation of Convolution Decoder.................................. 67
ix
Figure 29: Simulink implementation of R-S Decoder................................................ 68
Figure 30: BER Performance of BPSK with different CP.......................................... 71
Figure 31: BPSK result in term of Signal Strength and constellation diagram......... 72
Figure 32: BER Performance of QPSK(1/2) with different CP.................................. 33
Figure 33: BER Performance of QPSK(5/6) with different CP.................................. 75
Figure 34: QPSK result in term of Signal Strength and constellation diagram.......... 75
Figure 35: BER Performance of 16-QAM (1/2) with different CP........................... 78
Figure 36: BER Performance of 16-QAM (1/2) with different CP............................ 78
Figure 37: 16-QAM result in term of Signal Strength and constellation diagram.... 79
Figure 38: BER Performance of 64-QAM (2/3) with different CP............................ 81
Figure 39: BER Performance of 64-QAM (3/4) with different CP............................ 82
Figure 40: 64-QAM result in term of Signal Strength and constellation diagram..... 82
Figure 41: Probability of symbol error for the different transmitted power.............. 84
x
List of Table
Table 1: Literature Survey................................................................................... 10
Table 2: Comparison of IEEE standard for BWA............................................... 23
Table 3: 802.16-2004 MAC features.................................................................. 28
Table 4: 802.16-2004 PHY features.................................................................... 30
Table 5: Data source for AMC............................................................................ 37
Table 6: Mandatory channel coding per modulation............................................ 40
Table 7: Puncturing Vector for different convolution code................................. 47
Table 8: Normalization factors............................................................................ 50
Table 9: Modulation alphabet for the constellation map...................................... 50
Table 10: Customization Mapping......................................................................... 51
Table 11: BER Performance on various noise levels on different cyclic prefix..... 70
Table 12: BER Performance on various noise levels on different cyclic prefix..... 73
Table 13: BER Performance on various noise levels on different cyclic prefix..... 77
Table 14: BER Performance on various noise levels on different cyclic prefix...... 80
xi
List of Abbreviation Note: All the abbreviation in this thesis has been taken from the standard books
0-9 3G 3rd Generations
A AMC Adaptive Modulation & Coding
ARQ Automatic Repeat Request
ATM Asynchronous Transfer Mode
AWGN Additive White Gaussian Noise
B BER Bit Error Rate
BTC Block turbo coding
BPSK Binary Phase Shift Keying
BS Base Station
BWA Broadband Wireless Access
C
CC Convolution Code
CPS Common Part Sub-layer
CS Convergence Sub-layer
CTC Convolutional turbo coding
CP Cylic Prefix
CPE Customer Premises Equipment
D DES Digital Encryption Scheme
DL Down-Link
DSL Digital Subscriber Scheme
DFS Dynamic Frequency Selection
xii
F FDD Frequency Division Duplexing
FDM Frequency Division Multiplexing
FEC Forward Error Correction
FFT Fast Fourier Transform
G GF Galois Field
I IFFT Inverse Fast Fourier Transform
IP Internet Protocol
ISI Inter symbol Interference
L LOS Line of Sight
M MAC Medium Access Layer
MRC Maximum Ratio Combining
MC Mobile Code
MIMO Multiple Input & Multiple Output
MS Mobile Station
N NIST National Institute of Standard and Technology
N-LOS Non Line of Sight
O OFDM Orthogonal Frequency Division Multiplexing
OFDMA Orthogonal Frequency Division Multiple Access
P PDU Packet Data Unit
PHY Physical Layer
xiii
Q QAM Quadrature Amplitude Modulation
QoS Quality of Services
QPSK Quadrature Phase Shift Keying
R RF Radio Frequency
S SC Single Carrier
SAP Service Access Point
SDU Service Data Unit
SMS Short Messaging Services
SNR Signal to Noise Ratio
STC Space-Ttime Coding
SS Security Sub-Laier
T TDD Time Division Duplexing
TDM Time Division Multiplexing
U UL Uplink
V VoIP Voice over IP
W Wi-Fi Wireless Fidelity
WiMAX Worldwide Interoperability for the Microwave Access
WLAN Wireless Local Area Network
WMAN Wireless Metropolitan Area Network
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Chapter One
“Introduction to WiMAX”
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1.1 Introduction This chapter contains a brief description of the dissertation work along with some open
challenges issues of WiMAX and its mitigation. A short description about the structure of
dissertation is included at the end of this chapter.
1.2 Motivation
Sometimes ago, we were completely dependent on analog system, both the sources,
transmitter and receiver were on analog format but as the advancement of technology it is
made possible to transmit the data in digitize form. Along with the digital advancement,
the computer was getting faster towards fastest, the data carrying capacity and data rate
increased from kilobytes to megabytes. By emerging the concept from wire to wireless
and after investing so much money in researching, engineers became successful to invent
wireless transmitter and receiver for air communication. Applications like voice, Internet
access, e-mail, SMS, paging, file transferring, video conferencing, gaming and
entertainment etc became a part of life.
Mobile phone systems, WLAN, wide-area wireless network systems, ad-hoc wireless
networks satellite systems and the system where the channel interface is air are the
wireless communication systems, all these technology based on wireless technology to
providing higher throughput, vast mobility, wider coverage, robust backbone to thereat.
The vision is seen as a little bit more by the engineers to provide the smooth transmission
of multimedia anywhere on the globe through ubiquitous application and devices that’s
emergence a new concept for the wireless communication which is cheap and easy to
handle to work in all weather condition.
This is to be fact that, Broadband Access through DSL, T1-carrier or cable infrastructure
is not available especially in rural areas. With DSL we can covers only up to 18,000 or
19,000 feet after the 19,000 feet there is huge degradation in speed, this means that many
suburban and rural areas may not served. The Wi-Fi standard broadband connection may
solve this by some mean but not possible in everywhere due to coverage limitations. But
the Wireless Metropolitan-Area standard which is to be known as WiMAX can solve
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these limitations. The wireless broadband connection is much easier to deploy, that have
the capacity to address the long geographical area and have easier to access.
1.3 Problem Definition We know that the physical layer is most unreliable layer in any wireless system which is
responsible for error free delivery, so the error free communication in WiMAX is a
challenging task.
In order to achieve the higher throughput, we are trying to minimize the BER as much
as possible.
So to achieve the minimum BER, we must have the higher SNR.
But the problem is that we can improve the SNR at a certain limit as we are following
the cellular architecture.
Mitigation
So in order to achieve the solution we have to find the alternative solution to achieving
the minimum BER and the solution is, we can achieve the minimum BER by using the
different modulation and coding scheme (BPSK, 4-QAM, 16-QAM, and 64-QAM) with
different channel coding rate.
So, we measure the performance evaluation of Physical Layer of IEEE 802.16e.
SNR BER
1.4 Research Methodology
The Evaluation Methodology of IEEE 802.16e defines a unified method of simulation
models and associated parameters that can be used when introducing new proposals for
IEEE 802.16e or when presenting new research results. The simulation components can
introduce results both from the link-level perspective, when only one base station and one
mobile station exist in the network topology scenario.
The Physical layer which should be consisting of:-
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• Random Source
• Transmitting module
• Channel Module
• Receiving Module
We will use the simulink of MATLAB 7.9.0 (R2009b) environment for the simulation of
physical layer model. On the WiMAX physical layer we are using the channel encoding
for minimizing the error.
1.5 Application As we know WiMAX is the standard for Wireless MAN for BWA user, we are deal with
the Physical Layer which have greater advantage with OFDM that is enable to archive the
throughput in order to save the spectrum apart of this there are several applications some
of these are-
QoS with adaptive Modulation & Coding
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Wider Coverage Greater Throughput (Up to 73 Mbps at 20 MHz Channel) Advance Security Mechanism Lower Bit Rate at all channel condition Radio Resource Management
1.6 Thesis Contribution The goal of this project is to implement and simulate the OFDM Physical layer
specifications of IEEE 802.16e-2005 using Adaptive Modulation Techniques. We are
also analyzing the performance of OFDM physical layer in mobile WiMAX based on the
simulation results of-
Bit-Error-Rate , Signal-to-Noise Ratio and
Probability of Error (Pe).
After achieving the objective we are optimize the overall system by changing the system
parameter and finally we have to analyze that how much we have deal with BER, that’s
tell how our communication is more effective.
1.4 Outline of the thesis
This thesis examines the implementation of a WiMAX Physical layer built with Matlab
Simulink. This simulation is targeted to the n-point FFT. The thesis is organized in seven
chapters, in which a detailed overview of every communication block of the system is
taking into account both the standard and the corresponding theoretical aspects, which are
necessary to understand all the different methods and processes that have been used.
An overview of the WiMAX system and related issue with mitigation and methodology
has already been exposed in the present chapter and in chapter-2 we are describe the open
challenges and issues and classification of methods with relative advantages and
disadvantages.
Whereas the main features of the standard are summarized in chapter-3. To understand
the objectives and the applications of this system, a comparison between WiMAX and
other wireless systems is also included in the chapter.
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The remaining five chapters discuss the implementation and their resul of the WiMAX
simulator.
Like any other communication system, WiMAX has consist of three basic elements first
one is transmitter second is channel which is air interface in wireless communication and
third one is the receiver. The block diagram of a WiMAX communication system is
shown in Figure 1.
Figure 1: Basic communication system.
The transmitter and its component are presented in presented in Chapter 4, from
generating the symbol to be transmitted over the channel. Before sending it, the system
has to be adapted to the channel conditions by using a specific adaptive modulation
coding scheme which have to be more appropriate. As the modulated data is transmitted
through the OFDM transmission, it also needs to generate the OFDM symbol by IFFT
operations, which include a frequency-time transformation and the addition of a guard
period. Then, the information is send through the multicarrier technology over the
channel, discussed in the chapter 4.
Chapter 5 we are discussed about the communication channel. For the WiMAX system, it
is a wireless channel. The performance of any wireless communication system is highly
dependent on the propagation channel, and so, a detailed knowledge of radio propagation
effects, such as path loss, frequency-selective fading, Doppler spread, and multipath
delay spread have to be considered for the optimization of the communication link.
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The receiver is part is discussed in Chapter 6. It collects the signal after passing the
channel and performs the reverse operations of the transmitter to obtain the transmitted
information.
Chapter 7 analyzes the obtained results. Firstly, simulation results using an AWGN with
Multipath Fading channel are discussed and at last discussed the Probability of Error for
the AWGN channel with respect to the transmitted power at the ambient temperature.
Finally, the concluding remarks and Future work are summed up in Chapter 8.
Additionally, this work also includes two appendices that complete the thesis already outlined. Appendix A is intended to give an .m file codes whose output is use for the simulink scenario systems. Appendix B presents a Probability Error.
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Chapter Two
“Literature Review”
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In this chapter contains a brief description of Literature survey which have to be conclude
to find the open challenges in emergence of next generation wireless communication, and
also we are include some of latest research paper which is to be intended for finding the
mitigation in some of open issues.
2.1 Open Challenges and Key Issue
IEEE 802.16 is a set of telecommunications technology standards aimed at providing
wireless access over long geographical area by the various ways - from point-to-point
links to full mobile cellular type access. WiMAX covers a long area of several kilometers
that’s why it is also called WirelessMAN. Theoretically, a WiMAX base station can
covers a in range of up to 50 kms for fixed stations and 5 to 15 kms for mobile stations
with a maximum throughput of up to 73 Mbps [1], [2] compared to 802.11a with 54
Mbps up to several hundred meters, EDGE with 384 kbps to a few kms, or CDMA2000
(Code-Division Multiple Access 2000) with 2 Mbps for a few kms.
IEEE 802.16 standards group has been developing a set of standards for BWA for a
metropolitan area. Since 2001, several amendments are going through of standards that
have been published and are still being developed. Like other standards, these
specifications are also a compromise of various competing proposals and contain many
optional features and mechanisms. The Worldwide Interoperability for Microwave
Access Forum or WiMAX Forum is a group of 400+ service providers, component
manufacturers, networking equipment manufacturer vendors and users that decide which
of the legion options allowed in the IEEE 802.16 standards or not so that equipment from
different vendors are interoperable. Several features such as unlicensed band operation,
60 GHz operation, while specified in the IEEE 802.16 are not a part of WiMAX networks
so that these are not in the standard profiles by the WiMAX Forum. For an equipment to
be certified as WiMAX compliant, the equipment has to pass the inter-operability tests
specified by the WiMAX Forum. For the rest of this paper, the terms WiMAX and the
IEEE 802.16 are used interchangeably.
We we have include some of the latest research paper from the eminent publication-
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Table 1: Literature Review
S.No Title Author Publication Conclusion Platform [1] The
WiMAX 802.16e Physical Layer Model
Muhammad Nadeem Khan and Sabir Ghauri
IET International Conference on Wireless, Mobile and Multimedia Network; Jan 2009
In this paper the authoe prepare a WiMAX PHY layer model for fixed modulation scheme (4-QAM) with 5/6 CC rate and the performance will be based on BER for AWGN channel.
MATLAB simulink
[2] On QoS Aspects with Different Coding and Channel Condition for a WiMAX based Network
Vinit Grewal and Ajay K Sharma
IEEE 2nd International Conference on Advance Computing; March 2010
In this paper author simulate a physical layer scenario under the different modulation & coding scheme the result shall be described in the form of SNR impact on BER for the different channel.
OPNET Modulator
[3] Performance Simulation of IEEE 802.15e WiMAX Physical Layer
Mohamed A. Mohamed , Mohamed S. Abo-El-Seoud and Heba M. Abd-El-Atty
Second IEEE International Conference on Information Management and Engineering; Jan. 2010
Again in this paper author prepare a model for WiMAX PHY and obtaining the performance in term of BER for the different modulation and coding scheme.
MATLAB simulink
[4] An Analytical Approach to Qualitative Aspect if WiMAX Physical Layer
Arathi R. Shanker, Poonam Rani and Suthikshn Kumar
IEEE Second International Conference on Information Technology for Real World Problems;
In this paper the author prepare a model for the WiMAX PHY, the performance has been obtain in term of BER under the Rayleigh and Rician channel and
MATLAB
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June 2010 also evaluated the Pe for the same channel.
[5] A Survey on Next Generation Mobile WiMAX Networks: Objectives, Features and Technical Challenges
Ioannis Papapanagiotou,Dimitris Toumpakaris,Jungwon Lee and Michael Devetsikiotis
IEEE Communication Surveys & Tutorials; Fourth Quarter 2009
In this survey paper the author focused on the emerging trend of next generation mobile especially on WiMAX. In this paper the author also tells about the PHY layer specification with MIMO reception.
----------
[6] Performance Characteristics of an Operational WiMAX Network
James M. Westall and james J. Martin
IEEE Transactions on Mobile Computing, Vol. 10, NO.7, July 2011
In this paper the author evaluate the performance on different parameter of QoS(like throughput, latency ) for different type of traffic which shpuld be classified accordind to their preference all the QoS will check for the Adaptive PHY which have use multiple modulation & coding scheme.
OPNET Modulator
[7] Performance Parameter of Mobile WiMAX: A Study on the Physical Layer of Mobile WiMAX under Different
Omar Arafat and K. Dimyati
IEEE International Conference on Computer Engineering and Applications, Sep. 2010
In this paper the author measure the performance by developing a model, the performance will be evaluated in under the SUI(Stanford university interim ) channel model for
MATLAB
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Communication Channels & Modulation Technique
different SNR and evaluated the BER, the author iterate this process for the different guard time period.
[8] WiMAX Physical Layer: Specifications Overview and performance Evaluation
Mingxi Wang
Second IEEE CCNC Research Student Workshop, Jan. 2011
In this paper, the author given a brief overview of the physical layer specifications of the latest WiMAX standard IEEE 802.16-2009. A simplified simulation system of WiMAX OFDMA PHY with LDPC coded MIMO-OFDM is established For performance evaluation purpose. Simulations show that the Iterative receiver structure can achieve good performance. OFDM is established For performance evaluation purpose. Simulations show that the iterative receiver structure can achieve good performance. Channel should be considered as AWGN.
-
[9] A Nadine Second IEEE In this paper the The
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Comprehensive WiMAX Simulator
Abbas, Hazem Hajj and Ahmad Borghol
CCNC Research Student Workshop, Jan. 2011
author first classified the inbound traffic then classified traffic should be scheduled according to the priority then according to the priority resource will be provided the result is obtain in form of throughput and AMC.
proposed simulator is implemented using Borland C++ builder.
[10] A Physical layer simulator for WiMAX in Rayleigh Fading Channel.
Jamal Mountassir, Horia Balta, Marius Oltean , Maria Kovaci and Alexandru Isar
6th IEEE International Symposium on Applied Computational Intelligence and Informatics , May 19–21, 2011
The Author obtains the performance for the Rayleigh fading channel for non-mobility with physical layer specification.
MATLAB
[11] Simulation of Channel Estimation and equalization for WiMAX Physical layer in Simulink
Onsy Abdel Alim, Nemat Elboghdadly, Mahmoud M. Ashour and Azza M. Elaskary
First International Confrence on Computer Engineering and System; Oct 2007
Comparing the performances of all schemes by measuring bit error rate versus SNR with setup with 16QAM, as modulation scheme and multi-path fading and Doppler shift channels as channel models. Channel estimation based on LS algorithm, with the linear interpolation, the
MATLAB Simulink
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second order interpolation, the spine cubic interpolation and the low-pass interpolation.
[12] Y.Q. Bian,
A.R. Nix, Y.Sun and P. Strauch
Performance Evaluation of Mobile WiMAX with MIMO and Relay Extension
IEEE International Conference on Wireless Communication and Networking,; June 2007
In this Paper the author obtain the performance of mobile Wimax with 2x2 MIMO relay extension for a microcell with some assumption all the parameters are taken for the simulation is carried out from the standard documentation. For an urban macrocell (radius of 1.5km), around 92% of users were seen to experience SNR levels below this threshold, and hence would struggle to exploit Spatial Mutiplexing.
--------------
[13] Link-Level Simulation and Performance Estimation of WiMAX IEEE 802.16e
Wen-an ZHOU, Bing XIE and Jun-de SONG
Second International Conference on Pervasive Computing and Application; June 2009
In this paper the author prepares a Link-level Simulation and Performance Estimation of WiMAX
MATLAB
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IEEE802.16e PHY and obtains performance curves. The simulation results provide a reference value of PUSC gain. And also the whole link performance with QPSK and 16QAM.
[14] Performance of MIMO Antenna Technique IEEE 802.16e
Onsy Abdel Alim and Ahmed E Naggary
ITI 5th International Conference on Information Communication and Technology; June 2007
In this paper the author obtains the performance through the smart antenna technology which includes Beamforcing, space-time diversity code and spatial multiplexing. The author first presented antenna array techniques, which reduce interference and provide the diversity gain that enhances the useful signal SNR. Next, we gave a general description of Multi-Input Multi-Output systems that can be used for various purposes including
ADS Aglient
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diversity gain, and interference reduction.
Key issues of WiMAX Networks
There is some open issues in WiMAX networks that differentiate it from other
metropolitan area wireless access technologies are-
1) Its use of Orthogonal Frequency Division Multiple Access (OFDMA),
2) Scalable use of any spectrum width (varying from 1.25 MHz to 28 MHz),
3) Time and Frequency Division Duplexing (TDD and FDD),
4) Advanced antenna techniques such as beam forming, Multiple Input Multiple
Output (MIMO),
5) Per subscriber adaptive modulation,
6) Error Free Communication
7) Advanced coding techniques such as space-time coding and turbo coding,
8) Strong security and Multiple QoS classes
2.3 Classification of Methods In order to achieve the research objective there are several method, in our dissertation we
are go with the Physical Layer issue so to obtain the performance of WiMAX physical
layer with different channel encoding scheme and also including the OFDM we are
having two scheme as the methodology-
1) Analytical Approach
2) Simulation Approach
With both of scheme there is some pros and cons-
• Analytical Approach
Pros
Result is more accurate
No need of Computer environment
Based on some standard formulation
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Obtain the generalize the result
Cons
Hard to deal with Large Data
Hard to deal with Complex input
Iteration is taking the more time
Finding the error is too hard and time taking
Requirement of Skill workforce
• Simulation Approach
Pros
Result is more scalable
Computer environment save the time of computation
Easy to deal with large data
Computation of complex number is also easy
Iteration is helpful.
To readout the result no skill workforce is require
Cons
Result is not so more accurate
Simulation is bound with limitation
Generalize formulation is hard
2.4 Summary After go through with several research paper and discussed with our supervisor, I am
deciding to go with physical layer issue, because in any wireless environment physical
layer is the most unreliable layer which have to responsible for error free communication
so there is lot of scope.
By changing the parameter like channel encoding scheme, modulation scheme we can
enhance the performance of the overall system and also by iteration the simulation we
can optimize the system also.
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Chapter Three
“IEEE 802.16: Evolution and Architecture”
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This chapter contains the brief discusses of the evolution of the IEEE 802.16 standard for
WMAN. The protocol layer of the standard has been viewed to get the idea of relation
between different layers. This chapter ends with a overview of the IEEE 802.16 based
Physical and MAC layer specification with their Pros and Cons.
3.1 WiMAX at a Glance WiMAX is known as the next generation wireless broadband technology that offers high
transmission rate, secure, QoS sophisticate and last mile access broadband services along
with a cellular concept and Wi-Fi hotspots. The evolution of WiMAX began a few years
ago when engineers and researcher having the need of wireless Interface access and other
internet services which works ubiquitously especially in sub-urban areas or on those areas
where it is hard to establish wired infrastructure and economically not feasible.
IEEE 802.16 is also known as Wireless-MAN standard, explored both licensed and
unlicensed band of 2-66 GHz which is standard for both fixed and mobile broadband
application. WiMAX forum is a private organization which was formed in June 2001 for
the purpose of to coordinate and maintain the equipment and develops the instrument
those will be backward compatible and interoperable. After few years, in 2007, Mobile
WiMAX equipment developed with the standard IEEE 802.16e and got the certification
and they announced to publish the product in 2009 to provide the mobility for nomadic
user.
WiMAX have deputize other broadband technologies contending in the same section and
will get an advantages solution for the BWA in order to deploy the last mile access in
every places where on other hand it is hard to deploy with other technologies, like cable,
DSL, T-1 carrier and where the costs is always matter for the maintenance and
deployment of such technologies. In that way, WiMAX would provide the coverage in
the rural areas and underserved metropolitan areas in developing countries. It can be used
in backhaul for enterprise campus, Wi-Fi hot-spots and for a large institution. WiMAX
provide a excellent solution for these issue because it offers a cost-effective, rapidly
growing deployable solution [2].
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In addition to that, WiMAX will face a grievous competitor of 3G cellular systems with
high speed mobile data specification would be achieved with the 802.16e specification.
Figure 2: Possible scenarios for the deployment of WiMAX
3.2 Evolution of IEEE family of standard for Broadband Wireless
Access (BWA)
At the end of 90’s, many telecom gadgets manufacturers were start to develop the
equipment and offers products for BWA. But the Industry was suffered from an
interoperable problem due to this need of a standard, The U.S. NIST called a meeting to
discuss that topic in August 1998 [1]. The meeting had terminated with a decision to
organize within IEEE 802 standard. The endeavor was welcomed in WiMAX forum that
was leaded to constitution of the 802.16 Working Group. Since then, the Working Group
members have been developing lot of standards for fixed and mobile BWA. IEEE
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Working Group 802.16 on BWA standard is responsible for development of 802.16 and
the included Wireless Man air interface.
The IEEE 802.16 standard contains the of PHY and MAC layer specification. The first
version of the standard IEEE802.16 2001 [2] was release on December 2001 and it has
pass through with many modification to consisting the new features and securities. The
current version of the standard IEEE 802.16 2004 [3], release on September 2004, that
replace the all previous versions of the standards. This standard specifies the air interface
for fixed BWA systems with supporting multimedia services in licensee and unlicensed
spectrum [3]. The Working Group approved the amendment IEEE 802.16e2005 [4] to
IEEE802.16 2004 on February 2006. To understand the development of the standard to
its current stage, the evolution of the standard is presented here.
3.2.1 IEEE 802.16 2001
The first issue of the standard specifies a set of MAC and PHY layer specification that is
dedicated to providing the fixed broadband wireless access in a point-to-point or point-to-
multipoint topology [5]. Single carrier modulation technique is used by the PHY layer at
the 10-66 GHz frequency band.
Transmission slots, durations and modulations schemes are allotted by the BS and shared
with in the network. Subscribers need to stay within the coverage from the base station
that they are connected and do not need to listen any other node of the network. MS have
the ability to negotiate with the BS for bandwidth allocation on a burst by burst basis that
provides scheduling flexibility.
The standard consists of digital modulation scheme such as QPSK, 4-QAM, 16-QAM
and 16-QAM. These can be changed from frame to frame and from SS to SS, depending
on the channel condition. The standard supports both TDD and FDD technique.
Most important ability of 802.16-2001 is its characteristic to provide the QoS at the MAC
Layer. Traffic Flow identification does checks the QoS. Traffic flows are classified by
their QoS parameters, which can be used to specify parameters like low latency and
tolerated jitter [6]. Service flows can be originated either from BS or SS. 802.16-2001
works only for the L-O-S conditions with outdoor CPE.
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3.2.2 IEEE 802.16a 2002
The IEEE 802.16a-2003 is nothing but the some amends of IEEE 802.16-2001 by
enhancing the MAC layer to support various PHY layer properties to providing the
additional physical layer specifications. This was filtered out by WiMAX forum
organization in January 2003[7]. This amendment added physical layer support for 2-
11GHz band for both licensed and unlicensed bands. N-LOS operation becomes possible
due to inclusion of below 11 GHz band. Due to N-LOS operation multipath propagation
becomes a problem. To solve this problem multipath propagation and interference
mitigation features like advanced power management technique and adaptive antenna
arrays were included in the specification [7].The option of employing the OFDM was
included as an alternative.
In this version, some security feature was upgraded while in 802.16-2001 it was not
mandatory; many of security layers became added. IEEE 802.16a support for mesh
topology optimally in place of P-M-P.
3.2.3 IEEE 802.16c 2003
IEEE Standards certified the amendment of IEEE 802.16c [2] in December 2002. In this
amendment the WiMAX forum added the detailed profiles of 10-66 GHz and removes
some errors and incompatibility issues of the first version.
3.2.4 IEEE 802.162004
802.16-2001, 802.16a and 802.16c were consolidated and a new standard was formed
which is known as 802.16-2004. At the starting, it was revised under the name 802.16
REVd, but the changes were so unfeigned that the standard was released under the name
802.16-2004 on September 2004. With this version, the whole family of the standard is
signed and approved.
BER
When number of bits error occurs within one second in transmitted signal then we called
BER. According to some other books Bit Error rate is a type of parameter which used to
access the system which can transmit the digital signal from one end to another end. We
can define BER as follows,
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If transmitter and receiver’s medium are good in a particular time and SNR is high, then
Bit Error rate is very low. In our dissertation the simulation result will be in form of BER
aginst the different set of SNR.
Table 2: Comparison of IEEE standard for BWA
IEEE 802.16
2001
IEEE 802.16a IEEE802.16
2004
IEEE 802.16e
2005
Completed December
2001
January 2003 June 2004 December 2005
Spectrum 10-66 GHz 2-11 GHz 2-11 GHz 2-6 GHz
Propagation
/channel
conditions
LOS NLOS NLOS NLOS
Bit Rate
Up to 134
Mbps
(28 MHz
channelizatio
n)
Up to 75 Mbps
(20 MHz
channelization)
Up to 75 Mbps
(20 MHz
channelization)
Up to 15Mbps (5
MHz
channelization
Modulation QPSK,
16QAM
(optional in
UL),
64QAM
(optional)
BPSK, QPSK,
16QAM,
64QAM,
256QAM
(optional)
256 subcarriers
OFDM, BPSK,
QPSK, 16QAM,
64QAM,
256QAM
Scalable
OFDMA, QPSK,
16QAM,
64QAM,
256QAM
(optional)
Mobility Fixed Fixed Fixed/Nomadic Portable/mobile
Eb/E0
Energy per bit to noise power spectral density ratio is important role especially in
simulation. Whenever we are simulating and comparing the BER performance of
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adaptive modulation technique is very necessary Eb/N0. The normalized form of Eb/N0 is
SNR. In telecommunication, is the form of power ratio between a signal and background
noise.
Here P is mean power. If the signal and the background noise are measured at the same
point and if the measurement will take the same impedance then SNR will be getting by
measuring the square of the amplitude ratio.
BER Vs Eb/E0
The BER defined as the probability of error on the other hand SNR is the term of signal
power ratio between a noise powers. Some variables are described as under,
The error function (erfc)
The energy per bit (Eb)
The noise power spectral density (N0)
The value of error function is different for every modulation intrigue. That’s why every
modulation intrigue performs different behavior with respect to the background noise.
The higher modulation intrigue (like 64-QAM) is not beneficial for noise channel but it
accommodate the more data. On the other hand, the lower modulation scheme (like
BPSK) is more robust for noisy environment but data carrying capacity is too low.
The energy per bit (Eb) is defined by dividing the carrier power to measure of energy (in
joule). Noise power spectral density (N0) is the power per hertz (Joules per second). So, it
is clear from the definition that the dimension of SNR is cancelled. So the conclusion is
that, the probability of error is proportional to Eb/No.
3.2.5 IEEE 802.16e2005
This amendment was included in the current applicable version of standard IEEE 802.16-
2004 in December 2005. This includes the PHY and MAC layer specification to
combined fixed and mobile operation on the licensed band.
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3.3 Technical Overview The WiMAX standard defines the air interface for the IEEE 802.16-2005 specification
working in the frequency band 2-11 GHz. This air interface includes the definition of the
MAC and the physical (PHY) layers.
3.3.1 IEEE 802.16 Protocol Layers
The IEEE 802.16 standard is structured in the form of a protocol stack with well defined
interfaces. As shown in Figure 3, the MAC layer is formed with three sub layers:
Service Specific Convergence Sub-layer (CS)
MAC Common Part Sub-layer (CPS) and
Privacy Sub-layer.
The MAC CS receives higher level data through CS SAP and provides transformation
and mapping into MAC SDU. The WiMAX specification hits the two types of traffic
transportation through IEEE 802.16 networks: ATM and Packets. Thus, interfacing on
various protocols is available for multiple CS specification.
The core part of the MAC layer is CPS. The CPS performs the various function related to
the channelization, duplexing, accessing, framing, network topology and initialization.
This CPS offers the rules and mechanism for accessing the system, resource allocation
and connection maintenance. QoS scheduling and classification decisions are also
performed within the MAC CPS.
The security layer stands between the MAC CPS and the PHY layer. Security is a big
challenge for the wireless networks. MAC sub layer offers the cryptography mechanism
for protecting the information from unauthorized disclosure and is also used for
authorization and key management. Data, physical layer control and statistics are
exchange between the MAC CPS and the PHY through the PHY SAP.
The PHY layer includes multiple modulations and coding scheme, which is help to adapt
the instantaneous variation of the channel. Physical layer flexibility allows the system
designers to sartor their system according to the requirements. The physical layer
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describes the some mandatory profile that implemented with the system including some
optional features.
Figure 3: WiMAX Protocol Stack
3.3.2 MAC layer
Some functions are associated with providing service to subscribers. They have
transmitted the data in form of frames and have the control access of the common
wireless medium. The MAC layer, which is situated above the physical layer, groups the
mentioned functions.
Primarily work of the MAC is increase the performance by to accommodating multiple
physical layer specifications and their services, addressing the needs for different
environments. It is generally designed to work with point-to-multipoint networks,
through a base station that control independently. Access and resource allocation
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algorithms can be capable to carries hundreds of terminals on a single channel, terminals;
that may be shared by multiple users. Therefore, the MAC protocol defines how and
when a BS or a subscriber station may enlighten the transmission. At the time of
downlink there is only one user, and the MAC protocol is quite simple using TDM to
multiplex the data. In uplink, when more than one SS contend for accessing the channel,
then MAC layer protocol provide a mechanism that is a TDMA technique, thus providing
an efficient use of the bandwidth.
Figure 4: WiMAX Physical and MAC layer architecture
The services required by the multiple users are varied, including voice and data, IP
connectivity, and VoIP. In order to support this variety of services, the MAC layer must
accommodate both continuous and busty traffic, adapting the data velocities and delays to
the needs of each service. Additionally, mechanisms in the MAC provide for
differentiated QoS supporting the needs of various applications.
The services required by the multiple users are varied, including voice and data, IP
connectivity, and VoIP. In order to support this variety of services, the MAC layer must
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accommodate both continuous and busty traffic, adapting the data velocities and delays to
the needs of each service. Additionally, mechanisms in the MAC provide for
differentiated QoS supporting the needs of various applications.
Issues of transport efficiency are also addressed. Both modulation and coding schemes
are specified in a burst profile that is adjusted adaptively for each burst to each subscriber
station, making the use of bandwidth efficient, offers maximum throughput, and enhance
the system capacity. The radio resource allocation mechanism is designed to be scalable,
effective, and self- correcting, allowing the system scalability from one to hundreds of
users. Another transmission protocol that enhances the performance is the ARQ that
compatible with mesh topology rather than only point-to-multipoint network
architectures. The main advantage with mesh topology is that subscriber station direct
communication with other SS, so this topology increases the scalability of the system.
The specification also offers the automatic power control, and cryptography mechanisms.
Further detailed information of MAC could be found in [4] and [5].
Table 3: 802.16-2004 MAC features Feature Benefit
TDM/TDMA scheduled uplink/downlink frames
• Efficient bandwidth usage.
Scalable from one to hundreds of subscribers
• Allows cost effective deployments by supporting enough subscribers to deliver a robust business case Connection-oriented • Per connection QoS. • Faster packet routing and forwarding.
QoS support • Low latency for delay sensitive services (TDM, Voice, VoIP). • Optimal transport for VBR6 traffic (video). • Data priorization.
ARQ • Improves end-to-end performance by hiding RF layer induced errors from upper layer
t l Support for adaptive modulation • Enables highest data rates allowed by channel conditions, exploiting system capacity.
Security and encryption (Triple DES) • Protects user privacy.
Automatic power control • Enables cellular deployments by minimizing self-interference.
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3.3.3 Physical (PHY) layer
The IEEE 802.16-2005 standard defines three different PHYs that can be used in
conjunction with the MAC layer to provide a reliable end-to-end link. These PHY
specifications are:
• A single carrier SC modulated air interface.
• A 256-point FFT OFDM multiplexing scheme.
• A 2048-point FFT OFDMA scheme.
While the SC air interface is used for LoS transmissions, the two OFDM-based systems
are more suitable for NLoS operations due to the simplicity of the equalization process
for multicarrier signals. The fixed WiMAX standard defines profiles using the 256-point
FFT OFDM PHY layer specification. Furthermore, fixed WiMAX systems provide up to
5 km of service area allowing transmissions with a maximum data rate up to 70 Mbps in
a 20 MHz channel bandwidth, and offer the users a broadband connectivity without
needing a direct line-of-sight to the base station.
The main features of the mentioned fixed WiMAX are detailed next:
Use of an OFDM modulation scheme, which allows the transmission of multiple
signals using different subcarriers simultaneously. OFDM waveform is composed
of multiple narrowband subcarriers that are orthogonal to each other, frequency
selective fading is affected to a set of subcarriers that are easy to equalize.
Concept of an AMC mechanism that depends on channel conditions. It allows
changing the modulation and coding scheme that is more appropriate for optimum
throughput, thus making a most efficient use of the bandwidth.
WiMAX offers the both time and frequency division duplexing formats to enable
the system to be adapted to the regulations in different countries.
Robust FEC coding, used to minimize the effect errors in order to improve bit
error rate. The FEC scheme is implemented with a Reed- Solomon encoder
concatenated with a convolutional one, and followed by an interleaver. Optional
support of BTC and CTC can be implemented.
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Table 4: 802.16-2004 PHY features
Feature Benefit 256-point FFT OFDM waveform
• Simple equalization of multipath channels in Outdoor LoS and NLoS environments.
Adaptive modulation and variable error correction encoding per RF burst
• Ensures a robust RF link while maximizing the number of bits per second for each Subscriber unit.
TDD and FDD duplexing support • Addresses varying worldwide regulations when One or both may be allowed.
Flexible channel sizes (from 1.25 to 20 MHz)
• Provides the necessary flexibility to operate in many different frequency bands with Varying requirements around the world.
DFS support • Minimizes interference between adjacent Channels.
Designed to support AAS • Smart antennas are fast becoming more affordable, and as these costs come down, their ability to suppress interference and increase system gain is more important to BWA deployments.
TDM and FDM support • Allows interoperability between cellular Systems (TDM) and wireless systems (FDM).
Designed to support MIMO schemes
• Implemented in DL to increase diversity and capacity. • STC algorithms at the transmitter, MRC at the receiver.
Use of flexible channel bandwidths, comprised from 1.25 to 20 MHz, thus
providing the necessary flexibility to operate in many different frequency bands
with varying channel requirements around the world. This flexibility facilitates
transmissions over longer ranges and from different types of subscriber platforms.
In addition, it is also crucial for cell planning, especially in the licensed spectrum.
Optional support of both transmits and receives diversity to enhance performance
in fading environments through spatial diversity, allowing the system to increase
capacity. The transmitter implements STC to provide transmit source
independence, reducing the fade margin requirement, and combating interference.
The receiver, however, uses MRC techniques to improve the availability of the
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system.
Design of a DFS mechanism to minimize interferences.
Optional support of smart antennas, whose beams could be concentrated in a
particular direction or receiver intended directions, and therefore avoiding the
interference between co-channels, and enhance the spectral density and the BER.
Smart antennas are basically of two types, those have multiple beams (directional
antennas), and these are known as adaptive antenna array systems. The first ones
can use either a fixed number of beams; system choosing the most appropriate
beam direction for the transmission to the desired antenna. The second type is
with multi-element antennas with a adaptive beam pattern. These smart antennas
are becoming a good alternative for BWA deployments.
Implementation of channel quality measurements which help in the selection and
assignment of the adaptive burst profiles.
Support of both time and frequency division multiplexing formats (TDM and
FDM), to allow interoperability between cellular systems working with TDM, and
wireless systems that use FDM.
The mobile WiMAX uses the 2048-point FFT OFDMA PHY specification. It provides
service area coverage from 1.6 to 5 km, allowing transmission rates of 5 Mbps in a 1.75
MHz channel bandwidth, and with a user during the mobility. It presents the same
features as those of the fixed WiMAX specification that have been already mentioned.
However, other features such as handoffs and power-saving mechanisms are added to
offer a reliable communication. Battery life and handoff are two critical issues for
mobile applications. On one hand, maximizing battery life implies minimizing the mobile
station power usage. On the other hand, handoff and handovers are necessary to enable
the MS to shift from one cell to another at vehicular speeds without disconnecting the
connection.
Handoff is the main features of the IEEE 802.16 specification, and those of the so-called
fixed and mobile WiMAX, 802.16-2004 and 802.16e respectively, are summarized in the
following chart:[22]
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Figure 5: Convergence in wireless communications.
Sub-layers
WiMAX MAC layer is divided into three sub-layers such as Service Specific
Convergence Sub-layer, Common Part Sub-layer and Security Sub-layer.
Figure 6: Purposes of MAC Layer in WiMAX [32]
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3.4 PHY Layer Adaptation WiMAX technology is an IEEE 802.16 standard, which is responsible for providing the
Broadband Wireless Access (BWA) to the users as an alternative of the wired broadband.
The WiMAX provides fixed, nomadic, portable and mobile wireless broadband
connectivity without having the direct line-of-sight from the base station. It is different
from the previous versions of the WiMAX standard in that manner 802.16e adds the
feature of the mobility to the standard.
WiMAX technology supports adaptive modulation to regulate the Signal Modulation
Scheme which is depends on the SNR state of the radio link. When the radio link is
soaring in quality, the highest modulation scheme is opted which is offering the system to
avail additional capacity. And when the radio link is poor, the WiMAX system can move
to a lower modulation scheme to keep the connection stability [3].
The current channel condition report is send to the BS via reverse signal strength
indicator (RSSI) and, based on this report, a specific coding rate is opted for the data
transmissions thus, users who are having the bad channel condition, will be provided the
optimal coding rate that gives the maximum efficiency and better throughput. This
process is AMC.
Figure 7: Adaptive Modulation Scheme
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Chapter Four
“Transmitter”
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4.1 Physical Layer Model The Model of the WiMAX physical layer is build from the standard documentation [9,
10]. The model prepared in this dissertation is build under the defined parameters.
The modeling is created on MATLAB 7.9.0 (R2009b), Simulink 9 in Windows XP
SP2/Windows 7 operating system. MATLAB 7.9.0 (R2009b) Simulink consist all the
mandatory source blocks as from the standard documents. The Model includes three main
components namely transmitter, channel and receiver. Transmitter consists of channel
coding, modulation and sub-components whereas channel is modulated on AWGN and
Multipath Rayleigh Fading channel.
4.2 Transmitter
This section contains the different steps of the transmitter which should be performs
before transmitting the data. The blocks representations of the WiMAX transmitter
simulator are describe in Figure 9.
Figure 8: Transmitter of the WiMAX system
First of all, the data source is generated from the source is randomized and afterwards,
coded and mapped into QAM symbols. As previously explained in Chapter 1, the
simulator implemented in the thesis works for the Wireless MAN-OFDM physical layer
of WiMAX. This PHY layer uses OFDM with 256 subcarriers. Each OFDM symbol is
composed of 192 data subcarriers, one DC subcarrier, eight pilot subcarriers, and fifty
five guard carriers. So, the procedure of collecting the zero DC subcarrier, data, and
pilots is needed to build the symbols. Moreover, preambles consist of training sequences
Data Source
Channel Encoding
I-Q Mapping
Assembler
Add Zeros
IFFT Add CP
Training
Pilot
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that would be appended at the starting on each burst. These training sequences are used
for analyzing the channel estimation.
Figure 9: Physical Layer Scenario
4.3 Data Source
When we are go for the simulation then we will deal with the random source because in
actual system we can’t predict how much of data the user will used so for that model we
are select the input source by generating the random binary number number or
alternatively we have a choice with Bernoulli Binary block according to the AMC
requirement which is to be putting the simulink as MAC_PDU, standard is taken from
'ETSI TS 102 177 V1.3.2 (2006-03)’,[10] by running this ‘.m’ file we are generating
some parameter which is used as input for the other source, like primitive polynomial as
‘Prim_Poly’, generator polynomial as ‘Gen_Poly’ for R-S encoder, qamconst for M-ary
modulation.
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The number of bits that are generated is specified as frame-based and is calculated from
the packet size. The size of the packet depends on the OFDM symbol which is to be
transmitted and also overall coding rate, as well as the modulation M-ary. In equation 1
calculates the number of transmitted OFDM symbols in one frame. It depends on the total
number of transmitted symbols, NTsym that also consist the symbols used for the
preamble, specified by Ntrain:
NOFDM = NTsym − Ntrain. (1)
Furthermore, the total number of transmitted symbols is defined as
NTsym = . (2)
In the formula, Tsym is the OFDM symbol time, and Tframe denotes the frame duration.
The expression that defines Tsym as well as the possible values specified for the frame
duration, once the number of OFDM symbols is known, the number of bits to be sent by
the source is calculated:
Spacket = NOFDMRNdataMa. (3)
Here, R represents the overall coding rate, Ndata is the number of used data subcarriers,
and Ma defines the modulation alphabet, which is specified by the number of transmitted
bits per symbol.
Table 5: Data source for AMC
Modulation Overall Code Rate Data Source
BPSK 1/2 data_get=randint(11*8,1);
4-QAM 1/2 data_get=randint(23*8,1);
4-QAM 3/4 data_get=randint(35*8,1);
16-QAM 1/2 data_get=randint(47*8,1);
16-QAM 3/4 data_get=randint(71*8,1);
64-QAM 2/3 data_get=randint(96*8,1);
64-QAM 3/4 data_get=randint(108*8,1);
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4.4 Channel Encoding Small-scale link performance could be enhance by adding the redundant bits through the
channel encoding in the transmitting message so that if the data is corrupted by the mean
of instantaneous fading, the destroyed data may recovered at the receiver side. At the
transmitter side, baseband signal’s message sequence is mapped into the specific
sequence which is contain the larger number of bits (that’s called redundant bit, generally
represented by ‘k’) is added with the message, and then the coded message is modulated
for the transmission. [11]
Channel coding is used by the receiver to detect and correct some (or all) of the errors
introduced by the channel in a particular sequence of message bits. Because decoding is
performed after the demodulation portion of the receiver, coding can be consider to be a
post detection technique. The added coding bits lower the raw data transmission rate
through the channel (that is, coding expends the occupied bandwidth for a particular
message data rate). In WiMAX system channel coding is performed in three steps-
[1]. Randomization
[2]. Forward Error Correction
i. R-S Encoding
ii. Convolution Encoding
[3]. Interleaver.
4.4.1 Randomization
Randomization is the first process of the channel coding where the information bits of the
baseband must be randomized after receiving the data packet from the MAC, each burst
of the data is randomized before the transmission. The purpose of using randomizer is to
ignore the long sequence of zeros and ones. Randomization is performed on each burst
of data on a bit by bit basis. Randomization is implemented with the help of Pseudo
Random Binary Sequence generator with XOR gate which use the 15 stage shift register
with generator polynomial of the given equation in feedback configuration as shown in
figure 11. [3]
g(x) =1+x14+x15 (4)
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Figure 10: Channel Encoding- Randomizer with Shift Register
Forward Error Correction
The channel encoder carries out error-control coding for the purpose of protecting
information against error incurred as it progresses through the noise channel. This is
achieved by including additional information such that the channel decoder is able to
accurately recover the source information despite the presence of errors.
Forward Error Correction is applying on both the Uplink and Downlink bursts
which consist of R-S encoding and convolution encoding that improves the Bit Error
Rate (BER) performance. [11]
4.4.2 Reed-Solomon Encoding
The data is encoded by added some bytes through the Reed Solomon Encoder after the
randomization process, the calculation of this addition bits which is be helpful for
correction the baseband on the receiver side is based on Galois Field Computations, to do
obtain the redundant bits. Galois Field is widely used to represent data in error control
coding and is denoted by GF. WiMAX uses a dynamic R-S Encoding technique based on
GF (28) which is denoted as according to the table-.
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Table 6: Mandatory channel coding per modulation
Module AMC Modulation R-S code CC code rate Overall code rate
1 1. BPSK (12,12,0) 1/2 1/2
2 2. 4-QAM (32,24,4) 2/3 1/2
3. 4-QAM (40,36,2) 5/6 3/4
4 4. 16-QAM (64,48,8) 2/3 1/2
5. 16-QAM (80,72,4) 5/6 3/4
5 6. 64-QAM (108,96,6) 3/4 2/3
7. 64-QAM (120,108,6) 5/6 3/4
The purpose of using the Reed-Solomon codes is to minimize the error by scaling the
data using to add the redundancy bit to the data sequence. This redundancy bits provides
the addition helps in correcting the error that’s occur during the transmission. Reed-
Solomon is a coding scheme which works as it first constructing a polynomial from the
data symbols which is to be transmitted instead of the original baseband. The randomized
data are arranged in block format before passing through the encoder and a redundant
byte is appended according to the code rate.
The error correction capability of any RS code is determined by (n − k), the measure of
redundancy in the block. If the location of the corrupted symbols is not known in
advance, then the R-S code can correct up to t symbols. Where
t = (n − k)/2.
n= the total number of code symbols in the encoded block.
k = the number of data symbols being encoded,
(n, k) = (2m - 1, 2m - 1 - 2t)
For WiMAX the Reed-Solomon encoding shall be derived from a systematic R-S (n =
255, k = 239, t = 8) code using a Galois field specified as GF (28).
Where:
N = Number of Bytes after encoding
K = Data Bytes before encoding
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T = Number of bytes that can be corrected
The primitive and generator polynomials used for the systematic code are expressed as
follows [12, 13]
Code Generator Polynomial-
g(x) = (x+λ0) (x+λ1 ) (x+λ2) (x+λ3) ...... (x+λ2T-1) (5)
Field Generator Polynomial-
p(x) = x8 + x4 + x3 + x2 +1 (6)
Figure 11: General process of Reed-Solomon Encoder
The primitive polynomial is the one used to construct the symbol field and it can also be
named as field generator polynomial. The code generator is used the polynomial to
calculate parity and has the form specified as before, where is the primitive element of
the Galois field array over which the input information is overlap See [9] and [10] for
more information about Reed-Solomon codes.
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Figure 12: Process of shortening and puncturing of the RS code
To make the RS code flexible, i.e. to offer for the variable block sizes and variable
capability of error correction, it is passing through shorting and puncturing process.
When a block is shortened to k bytes, 239−k zero bytes are added as a prefix, and, after
the encoding process, the 239−k encoded zero bytes are deselected. After the shorting
process, the number of symbols goes out from the R-S encoder. With the puncturing,
only the first 2t of the total 16 parity bytes shall be employed. Figure 16 shows the RS
encoding, shortening, and puncturing process.
The input of the RS encoder block defined by Simulink that is specified by a vector
whose length is multiple of an integer of lk, where l the length of the binary sequences
with regarding the Galois field GF(2l), and the output is also specified by a vector whose
length is multiple of an integer. Therefore, the first step in this process is to divide the
message vector in a number of blocks sizes those lengths fits according to the quoted
requirement. On the same time, it has been noticed that the number of message bytes
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before the encoding, k, the number bytes after encoding is n, and the number of message
bytes which is to be corrected is t, are the specified in Table 6, and they change for every
modulation scheme. Thus, the number of blocks used in the Reed-Solomon encoder is
calculated as
NRS = .
A block diagram of the Reed-Solomon encoder implemented in Matlab Simulink is
depicted in Figure 14.
Figure 13: simulink scenario of the Reed-Solomon encoder of WiMAX
First of all output of randomizer is converted to the integer from the binary then all the
integer values are arrange the input data for the RS encoder in a matrix form, the number
of rows is calculated through the block size length before the encoding, k, and the
number of calculated Reed-Solomon blocks, as specified in Equation, determines the
number of columns. Zero padding is added from the beginning to achieve a length of 239
bytes for the R-S encoding block. The "Select rows"-block deals with selecting the
correct amount of bytes after the encoding process. Thus, the zero prefix is discarded, and
data is punctured by taking only the first 2t bytes of the total parity bytes, as previously
explained. To end, all the selected output is again transformed into the binary, and then it
is ready for the convolutional coding.
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Figure 14: simulink implementation of Reed-Solomon encoder of WiMAX
4.4.3 Convolution Encoding
Convolution codes are differ from block codes in that the encoder output is constructed
not from a single input but also using some of the previous encoder input. Convolution
codes are used for correcting the random errors in the data transmission. A convolution
code is a type of FEC code that is specified by CC (m, n, k), in which each m-bit
information symbol to be encoded and is transformed into an n-bit symbol, where the
n≥m and code rate is defined as m/n and the k is function of transformation of the last k
information symbols, where k is the constraint length (which is represent by the shift
register) of the code [11].the most basic diagram of convolutional coding is understand in
the figure.
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In WiMAX PHY RS block is encoded by the convolutional encoder, which has encoded
rate according to the table-1, Convolution encoder has two binary adders X and Y and
uses two generator polynomials, A and B. This generator polynomial is defined as [2, 3]:
A = 171 octal = 1111001 binary for X (7)
B = 133 octal = 1011011 binary for Y (8)
WiMAX uses the native code rate of 1/2, with constraint length of 7 which is show the
length of shift register.
Figure 15: block diagram of convolution encoder
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Figure 16: Convolutional encoder of binary rate 1/2
Figure 17: Convolutional encoder implementation in simulink
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4.4.4 Puncturing Process
Puncturing is done at the output of the convolutional encoder for deleting the additional
bits from the output stream of a convolutional encoder to reduce the length of the
message to be transmitted, thus Output of the convolution encoder is then punctured to
ignore the redundant bits from the encoded burst. The removed bits are dependent on the
code rate used. In order to produce the variable code rate a puncturing operation is done
on the output of the convolution encoder in accordance to Table 7.
Table 7: Puncturing Vector for different convolution code
The purpose of using the puncturing is obtain the variable coding rates. The
different rates that can be used are rate 1/2, rate 2/3, rate 3/4, and rate 5/6. In Table-3
denotes that the corresponding convolution encoder output is used, while “0” denotes that
the corresponding output is not used or deleted. On the receiver end Viterbi decoder is
used to decode the convolution codes.
4.4.5 Interleaving
Data interleaving is generally used to scatter error bursts. its most basic form can be
defined as a randomizer but it is quite different from the randomizer in the manner that it
does not change the state of the bits but it works on the position of bits and thus, reduce
the error concentration to be corrected with the purpose of increasing the efficiency of
FEC by spreading burst errors which is introduced by the transmission channel over a
longer time.
Interleaving is done by spreading the code symbols in time, before the transmission. The
incoming data in the interleaver is randomized done in two step permutations. First
permutation ensures that adjacent bits are mapped onto the non-adjacent subcarriers. The
Rate Puncturing Vector
1/2 [1; 1]
2/3 [1; 1; 0; 1]
3/4 [1; 1; 0; 1; 1; 0]
5/6 [1; 1; 0; 1; 1; 0; 0; 1; 1; 0]
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second permutation maps the adjacent coded bits onto less or more significant bits of
constellation thus avoiding long runs of less reliable bits.
The block interleaver interleaves all encoded data bits with a block size corresponding to
the number of coded bits per OFDM symbol. The number of coded bits depends on the
modulation technique used in the Physical layer. WiMAX 802.1 6 supports 4 modulation
techniques and is adaptive in the selection of a particular technique based on the channel
conditions and data rate. [3]
WiMAX 802.16e defines two permutations for the interleaver.
The first permutation is defined by the formula:
ink =(Ncbps/ 12) * mod(k, 12) + floor(k/ 12) (9)
The second permutation is defined by the formula:
s = ceil (Ncpc/2) (10)
jk = s * floor(mk / s)+(ink + Ncbps - floor(12 x mk / Ncbps ))mod(s) (11)
Where:
Ncpc = Number of coded bits per carrier
Ncbps = Number of coded bits per symbol
k =Index of coded bits before first permutation
mk =Index of coded bits after first permutation
jk =Index of coded bits after second permutation
WiMAX uses an interleaver that combines data using 12 interleaving levels. The effect of
this process can be understood as a spreading of the bits of the different symbols, which
are combined to obtain the new symbols with, rearranged the bits buts on same size. The
interleaving process in the simulator has been deployed in two steps. First, the data go
through a matrix which performs block interleaving through filling a matrix by the input
symbols in row by row, and then it send that matrix content in column manner. The
parameter which is used for this block is the number of rows and columns that compose
the matrix:
Nrows=12, Ncoloums=
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The second step consists of a block interleaver. It rearranges the elements of its input
according to an index vector. This vector is defined as
I= (12)
Where:
• is the total number of coded bits
=
• Ncpc is the number of coded bits per subcarrier, being the same as specified with
the modulation alphabet, Ma,
• Ntx-data is the total number of transmitted data symbols, and
Ntx-data = NdataNOFDM
• S=
4.5 I-Q Mapper
In M-ary PSK modulation, the amplitude of the transmitted signal was remaining
constant, thereby conceding a circular constellation. A new modulation scheme called
quadrature amplitude modulation is obtained when the phase is varying on different
amplitude. In figure 5 shows the constellation diagram of 2-ary, 4-ary and 16-ary QAM.
[11]
The constellation consists of a square lattice of signal points. The general form of an M-
ary QAM signal can be defend as
Si (t) = + (13)
0≤t≤T i= 1, 2… M
The purpose interleaver is to rearrange the data stream and sends the data frame to the IQ
mapper. The function of the IQ mapper is to map the incoming bits from interleaver on to
the constellation. Once the signal has been coded, it enters the modulation block.
Modulation scheme is the primary need of any wireless system to map coded bits on to
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the carrier that can be effectively transmitted over channel. The IQ plot for a modulation
scheme shows the transmitting vector for all combinations of data word. Gray coding is a
method for this allocation so that adjacent points in the constellation only differ by a
single bit.
The adaptive modulation and coding scheme is used in the DL and UL are binary phase
shift keying (BPSK), 4-QAM, and 16-QAM to modulate bits to the constellation points.
The PHY specifies seven combinations of modulation and coding rate, which can be
allocated to each subscriber according to the channel condition, in both UL and DL [9].
There are tradeoffs between data rate and robustness, depending on the channel
conditions.
To achieve equal average symbol power, the constellations described above are
normalized by multiplying all of its points by an appropriate factor Cm. Values for this
factor Cm are given in Table 8.The modulation mapping is built in the simulator by a
Simulink block implemented as a Matlab m-file. The symbol alphabet, As, represents the
coordinate points in the constellation map and is defined in Table 9.
Table 8: Normalization factors
Modulation Scheme Normalization constant for unit average power
BPSK Cm = 1
4-QAM Cm = 1/√2
16-QAM Cm = 1/√10
64-QAM Cm = 1/√42
Table 9: Modulation alphabet for the constellation map
Modulation Scheme Symbol alphabet
BPSK As = (1,−1)
4-QAM As = (1 + j, 1 − j,−1 + j,−1 − j)
16-QAM A = (j, 3j,−j,−3j)
As = (A + 1,A + 3,A − 1,A − 3)
64-QAM A = (j, 3j, 5j, 7j − j,−3j,−5j,−7j)
As = (A + 1,A + 3,A + 5,A + 7,A − 1,A − 3,A − 5,A − 7)
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Figure 18: BPSK, 4-QAM and 16-QAM constellation map
Moreever, an adaptive modulation and coding mechanism which is used for downlink
channel quality through allowing the number of transmitted bits per symbol that is
depending on the channel conditions.
Simulink Implementation
In our model we are use the customized I-Q mapper through the .m file whose output
from workspace is putting on the simulink model, customization is done according to
table-
Table 10: Customization Mapping.
Modulation Scheme Customization Constellation
BPSK
Ry=[+1 -1];
Iy=[0 0];
qamconst=complex(Ry,Iy);
qamconst=qamconst(:);
bitspersymbol=1;
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4-QAM
Ry=ones(2,1)*[+1 -1];
Iy=([+1 -1]')*ones(1,2);
qamconst=complex(Ry,Iy);
qamconst=qamconst(:)/sqrt(2);
bitspersymbol=2;
16-QAM
Ry=ones(4,1)*[+1 +3 -1 -3];
Iy=([+1 +3 -3 -1]')*ones(1,4);
qamconst=complex(Ry,Iy);
qamconst=qamconst(:)/sqrt(10);
bitspersymbol=4;
64-QAM
Ry=ones(8,1)*[+3 +1 +5 +7 -3 -1 -5 -7 ];
Iy=([+3 +1 +5 +7 -3 -1 -5 -7 ]')*ones(1,8);
qamconst=complex(Ry,Iy);
qamconst=qamconst(:)/sqrt(42);
bitspersymbol=6;
4.6 Principle of OFDM Transmission OFDM is a multiplexing technique that divides a channel with a higher relative data rate
into several orthogonal sub-channels with a lower data rate. For high data rate
transmissions, the symbol duration Ts is short. Therefore ISI due to multipath
propagation distorts the received signal, if the symbol duration Ts is smaller as the
maximum delay of the channel. To mitigate this effect a narrowband channel is needed,
but for high data rates a broadband channel is needed. To overcome this problem the total
bandwidth can be split into several parallel narrowband subcarriers. Thus a block of N
serial data symbols with duration Ts is converted into a block of N parallel data symbols,
each with duration T = N×Ts. The aim is that the new symbol duration of each subcarrier
is larger than the maximum delay of the channel, T > Tmax. With many low data rate
subcarriers at the same time, a higher data rate is achieved. In order to create the OFDM
symbol a serial to parallel block is used to convert N serial data symbols into N parallel
data symbols. Then each parallel data symbol is modulated with different orthogonal
frequency subcarriers, and added to an OFDM symbol, [4].
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Using Inverse FFT to Create the OFDM Symbol All modulated subcarriers are added together to create the OFDM symbol. This is done
by an IFFT. The advantage of using IFFT is that the system does not need N oscillators to
transmit N subcarriers.
The IFFT is used to obtain the signal in time domain, after modulation the produce
symbols obtained can be considered the amplitudes of sinusoids in a certain range. Before
applying the IFFT algorithm; each of the discrete samples corresponds to an individual
subcarrier. Apart of maintaining the orthogonality of the OFDM subcarriers, the IFFT is a
rapid way for modulating these subcarriers in parallel, and so, the use of multiple
modulators and demodulators, operation, is avoided. Before deploying the IFFT
operation in simulator, the subcarriers are rearranged. Figure 20 shows the subcarrier
structure that enters the IFFT block after performing the cited rearrangement. As seen in
the following figure, zero subcarriers are kept in the center of the structure.
Before doing the IFFT operation in the simulator, the subcarriers are rearranged. Figure
20 shows the subcarrier structure that enters the IFFT block after performing the cited
rearrangement. As seen in the following figure, zero subcarriers are kept in the center of
the structure.
Figure 19: Rearrangement performed before realizing the IFFT operation.
Cyclic Prefix Insertion
The cyclic prefix is used in OFDM signals as a guard interval and can be defined as a
copy of the end symbol that is inserted at the beginning of each OFDM symbol. Guard
interval is applied to mitigate the effect of ISI due to the multipath propagation. Figure
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21 shows the symbol and its delay. These delays make noise and distort the beginning of
the next symbol as shown.
To overcome this problem, one possibility is to shift the second symbol furthers away
from the first symbol. But existence of a blank space for a continuous communication
system is not desired. In order to solve this problem a copy of the last part of the symbol
is inserted at the beginning of each symbol. This procedure is called adding a cyclic
prefix. Figure 22 shows the insertion of a cyclic prefix. The Cyclic prefix is added after
the IFFT at the transmitter, and at the receiver the cyclic prefix is removed in order to get
the original signal. A detailed mathematical explanation can be found in [4].
Figure 20: Delay from front symbol
Figure 21: Cyclic prefix insertion.
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The robustness of any OFDM transmission is achieved by having a long symbol period to
minimizing the inter-symbol interference against multipath delay spread. Figure 23
depicts one way to perform the cited long symbol period that creating a cyclically guard
interval where each OFDM symbol is introduced by a periodic extension of the signal.
This guard interval is nothing but a copy of the last portion of the data symbol is known
as the cyclic prefix.
Copying the end of a symbol and appending it to the start results in a longer symbol time.
Thus, the total length of the symbol is
Tsym = Tb + Tg, (14)
Where:
• Tsym is the OFDM symbol time,
• Tb is the useful symbol time, and
• Tg represents the CP time.
The parameter G defines the ratio of the CP length to the useful symbol time. When
eliminating ISI, it has to be taken into account that the CP must be longer than the
dispersion of the channel. Moreover, it should be as small as possible since it costs
energy to the transmitter. For these reasons, G is usually less than 1/4:
G = (15)
The OFDM symbol enforces the source symbols to perform the operation into time-
domain. If we chose the N number of subcarriers for the system to evaluate the
performance of WiMAX the basic function of IFFT is to receive the N number of
sinusoidal and N symbols at a time (i.e. it converts the frequency domain signals into
time domain. These time domain signals are then transmitted through the channel.) The
output of IFFT is the total N sinusoidal signals and makes a single OFDM symbol. The
mathematical model of OFDM symbol defined by IFFT which would be transmitted
during our simulation as given bellow:
(16)
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Figure 22: OFDM symbol with the cyclic prefix
Figure 23: Generating the OFDM symbol using the IFFT
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Chapter Five
“Channel”
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5.1 Radio Channel When communicating over a wireless radio channel the received signal cannot be simply
a copy of the transmitted signal that is corrupted by channel. Instead signal fading occur
caused by the time-varying characteristics of the propagation environment. In this way,
random fluctuations caused by signal scattering due to the Non-LOS propagation
environment lead a phenomenon known as multipath fading. Signal that undergo either
flat or frequency-selective fading introduce the time dispersion in its self in multipath
environment. Moreover, the time dispersion is demonstrate by spreading in time of the
modulating symbols that introduced the inter-symbol interference. To avoid ISI, the
cyclic prefix time has to be chosen larger than the maximum delay spread of the channel.
Figure 24: Signal Losses due to three Effects
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5.2 Channel Model In order to measure the performance of the emergence communication system, a precise
description of the wireless channel is required to give its propagation environment. The
radio structure of a communication system plays very important role in the modeling of a
channel. The wireless channel is characterized by:
• Path loss (including shadowing)
• Multipath delay spread
• Fading characteristics
• Doppler spread
• Co-channel and adjacent channel interference
All the model parameters are random in nature and only a statistical characterization of
these parameters is possible in terms of the mean and variance value and these are
dependent upon terrain, tree density, antenna height, beam width (BW), wind speed and
time of the year.
Path loss
Path loss is affected by several factors such as terrain contours, distinct environments like
(urban or rural, vegetation and foliage), propagation medium (dry or moist air), the
distance between transmitter and receiver, height and location of antennas, etc. It has only
effect on the link budget [11] that is why we cannot consider it in the channel modeling.
Multipath Delay Spread
Due to the non NLOS propagation nature of the WMAN OFDM, we have to give
multipath delay spread in our channel model. It results due to the scattering behavior of
the environment. This multipath delay spread is a parameter which is used to signify the
effect of multipath propagation. It totally depends on the terrain, distance, antenna
directivity and other factors. The R.M.S delay spread value can span from tens of nano
seconds to microseconds.
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Fading characteristics
In a multipath propagation environment, the received signal detects fluctuation in signal
amplitude, phase and angle of arrival. The effect of this fluctuation is described by the
term multipath fading. Due to fixed arrangement of transmit and receive antenna, we
have to address the small scale fading in this channel model. Small scale fading gives to
the striking changes in signal amplitude and phase that could be experienced as a result of
small changes (as small as a half wavelength) in the spacial positioning between the
receiver and a transmitter.
Small scale fading is called Rayleigh fading if there are multiple reflective paths which
are large in number and there is no LOS signal component, the envelope of that received
signal is statistically explained by a Rayleigh Pdf. When a dominant non fading signal
component is present, such as a LOS propagation path, the small scale fading envelope is
also obtained by a Rayleigh Pdf [14]. In other words, the small scale fading statistics is
said to be Rayleigh whenever the LOS path is blocked and Multipath otherwise.
Doppler Spread
In a fixed wireless access, a Doppler frequency shift is formed on the signal due to
movement of the tiny objects in the environment. Doppler spectrum of wireless channel
differs from the exits mobile channel [12]. It has derived that the Doppler spectrum is in
the 0.12 Hz frequency range for fixed wireless channel. The shape of this spectrum is
also different than the classical Jake's spectrum for mobile channel.
With the above channel parameters, coherence distance, co-channel interference, antenna
gain reduction factor are addressed for channel modeling.
The primary requirements for that channel model, we have two options to go with. First,
we can use a mathematical model for each of them and second we can choose an
empirical model that is needed of the above requirements.
Description of the fading channel
The realistic wireless radio environment, a single received signal is composed of a
number of scattered waves, caused by the reflection and diffraction of the original
transmitted signal by objects in the surrounding geographical area. These multipath
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waves are combined at the receiver to give a resultant signal that can widely vary in
signal amplitude and phase. The Physical factors which are influencing the characteristics
of the fading experienced by the transmitter that are multipath propagation, mobility of
the reflecting objects and scatterers, and the relative motion between transmitter and
receiver. The presence of these reflecting objects and scatterers in the wireless channel
causes a change in the propagation environment and this changing environment also
alters the signal energy in amplitude, phase, and time and as a consequence, multipath
propagation occurs causing signal fading. The transmitted signal arrives at the receiver
through the multiple propagation paths, each of which has an associated time delay.
Because the received signal is spread with time due to the multipath scatterers are at
different delays, so that channel is said to be time dispersive. The difference between the
largest and the smallest among these delays introduce the maximum delay spread. On the
other hand, whenever the receiver and the transmitter are in relative motion, the received
signal is subjected to a constant frequency shift is called the Doppler shift. Therefore, as
it occurs in the time domain, the Doppler spread is defined as the difference between the
largest and the smallest among frequency shifts.
Fig. 25: Simulink Implementation
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Chapter Six
“Receiver”
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As seen in Figure 27, the receiver basically performs the reverse operation as the transmitter as well as channel estimation necessary to reveal the unknown channel coefficients. This section explains the different steps performed by the receiver to reconstruct the transmitted bits.
Figure 26: Block Diagram of Receiver
6.1 OFDM De-mapping
Firstly, the CP is removed and the received signal is converted to the frequency domain
using, in this case, the FFT algorithm. As it has been previously Section, an OFDM
symbol is composed by guard bands, data, pilots and the DC subcarrier. So a process is
requiring separating all the subcarriers. So in this order, at the decoder side first the guard
band is removed then to achieve pilots, data, and trainings disassembling is performed.
The training sequence is used to estimate the channel, through which manipulate the
channel coefficients. The calculated channel coefficient is used at the demapper side to
perform an equalization process and so this compensates the fading on the multipath
propagation channel. Once the data has been demapped, it go for the decoding process.
Fast Fourier Transform algorithm
The IFFT algorithm represents a rapid way that modulated parallel subcarriers. The FFT
or the IFFT are the pair of linear processes, so t is require converting the signal again to
the frequency domain by the mean of FFT.
Remove CP
FFT Disassembler
Demapper Decode Derandomizzer
Channel Estimation
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Removing the guard bands
When removing the subcarriers corresponding to the guard bands, the frequency structure
has been taken into account. Although zero padding appended at the end of the subcarrier
which is acting as a guard band is perform at the transmitter end, subcarriers is rearrange
when performing the IFFT operation, as display in Figure 27. Thus, the guard bands are
discarded at the middle of the OFDM symbol that is where they are allocated after the
arranging process.
Disassembler
The disassembler deals with the task of separating the signal, either in time or in
frequency domain, to get data, training, and pilots. These three different symbol streams
form the output of the disassembler.
6.2 IQ De-mapping At the receiving end of the communication link the demapper allowing the interface
between the channel and the functions that estimates the transmitted data bits for the user.
Moreover, the demapper operates on the received waveform that produces a set of
numbers that represent an estimatation of a transmitted binary for M-ary symbol. Thus,
the demapping process is used for making decision metrics about which bit is "zero" or
which bit is “one". This decision metric can be as simple decoded with hard decision, and
more complex, with soft decision.
With hard demapping the output of a hard decision has the function of the input, and this
form of output is application-dependent. However, the output of a soft decision
demapping is a real number, in form of a log-likelihood ratio. This is the logarithm ratio
between the likelihood of target produced the input and the likelihood of non-target
produced the input. In contrast, this form of output is application-independent in the
sense that this likelihood ratio output can theoretically be used to make optimal decisions
for any given target prior.
6.3 Channel Decoding The final stage of receive processing is the decoder. A block diagram of the decoder is
depicted in Figure-
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Figure 27: Block Diagram of channel Decoding
The decoder accepts the sequence of bits from the demapper process for next in
accordance with the encoding method. As the encoder block, the decoder is deployed in
four steps, which perform opposite operations with the purpose of retrieve the
information done by the encoder.
6.3.1 Deinterleaving
The deinterleaver rearranges the bits from each burst in the right manner by ordering
them serially before the interleaving process. Deinterleaving is of two types, a general
block deinterleaver and a matrix deinterleaver. Both of them work similarly as the ones
used interleaveing process according to the pair of transmitter and receiver. In general
block deinterleaver the elements of its input are rearranges according to the index vector.
The parameters used in both transmitter and receiver are the same as those ones used in
the interleaving process.
6.3.2 Inserting zeros
The block named "Insert Zeros" deals with the task of reversing the process performed by
the "Puncture" block. The puncturing process is used to deleting bits from the data
stream. The receiver did not know the position of the deleted bits but it could be know
their position through the puncturing vectors. Thus, zeros are used to fill the
corresponding vacancy of the stream in order to achieve the same code rate as before the
puncturing process. The puncturing can also be viewed as erasures from the channel.
They have no influence on the metric calculation of the succeeding Viterbi decoder
described in the following section.
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6.3.3 Viterbi decoder
The Viterbi algorithm reduces the manipulation overhead by taking the advantage of the
of the trellis code. Another advantage is its complexity, which is not the function of the
number of symbols. The Viterbi decoder performs approximate maximum likelihood
decoding. It involves calculating a measure of distance between the received signal at
time ti, and all the trellis paths entering each state at the same time.
The algorithm performs by discarding those trellis paths that could not possibly be part
for the maximum likelihood choice. When two paths enter the same state, the one is
chosen as the "surviving" path that has the best metric. The selection of the dissimilar
"surviving" paths is performed for all the states. The decoder continues perform in this
way to deeper into the trellis by making decisions through eliminating the least likely
paths. The early rejection of unlikely paths is avoiding the complexity. The goal of
selecting the optimum path can be expressed as choosing the codeword with the
maximum likelihood metric, or as selecting the codeword with the minimum distance
metric.
Moreover, the delay is introduced at the decoding process has been taken into account.
The rejection of possible paths does not process again until the third step in the
representation of trellis diagram. This is due to the fact that two branches cannot have
converged in one state so no decision can be made. This delay effect is considered in a
parameter called trace-back depth, which specifies how many symbols may precede the
beginning of the algorithm. For code rates of 1/2, a typical value for the trace-back depth
is about five times the constraint length of the code.
Another parameters of the Viterbi decoder block in the Simulink are used the trellis
structure for decoding the convolutional encoder, the decision type for decoding and the
operation mode for performing the process are defined as under:
• The types of signals that can support the Viterbi decoder are based on the decision
type parameter. The decision parameter can be of three types that have offered by
the simulink: unquantized, hard-decision and soft-decision.
• As the decision process that has been deployed in the demapper, the last kind of
decision is "unquantized", is one of them that are used by our simulator. It accepts
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real numbers on decoder block. The positive numbers are indicates as a logical 0,
and the negative number gives the logic 1. Whenever the decision parameter is set
to "soft-decision", the entries of this block are integers between 0 (most confident
decision for logical zero) and 2b (most confident decision for logical one), where
b is the number of soft-decision bits.
• The operation mode controls which method the block uses for transitioning. The
"truncated" mode, in this mode each frame is process independently and the
traceback depth parameter lye between starts at the state with the best metric and
the ends in the all-zeros state.
• Other values for this parameter are the "continuous" and "terminated" modes.
Figure 28: Simulink implementation of Convolution Decoder
6.3.4 Reed-Solomon decoder
The last part of the decoding process is the Reed-Solomon decoding. It processes the
mandatory operations to retrieve the signal and obtain at the end. As in the entire in
receiver blocks, the RS decoder performed the opposite operation corresponding to the
encoding block, explained in previously. Thus, the RS decoder takes codeword’s of
length n, and, after decoding the signal, it returns messages with length of k being n =
68 | P a g e
255 and k = 239, the same as in the RS encoder. Therefore the implementation for the RS
decoder has been performed with a Matlab simulink and s-function using the m-file. The
block diagram of the RS decoder is depicted in Figure 30.
Figure 29 Simulink implementation of R-S Decoder
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Chapter Seven
“Result & Analysis”
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7.1 Performance Evaluation
Based on the model presented in this dissertation, and tests carried out, the performance
was established based on 10 thousand symbols in each case. The performance is
displayed in the following figure in terms of the BER versus SNR logarithmic plot, time-
scatter plots for each module; Signal-to-Noise Ratios, time-scatter plot for the output
from the transmitter and FFT scope diagram for the transmitted signal.
The BER plot obtained in the performance analysis showed that model works well on
according to the channel condition. The time-scatter plots demonstrate the scattering of
the transmitted and received signals at different values of the Signal-to-Noise Ratios. It
also shows that at very low SNR the symbols are very difficult to recognize.
Module-I
Parameter (BPSK- 1/2)
• Modulation scheme:: BPSK
• Source:: Random Number (randint(11*8,1); )
• R-S Coding Rate:: No Need (12,12,0)
• Convolution Encoding:: 1/2
• Interleaving:: [1; 1]
• FFT Size:: 256
• Channel:: 16
• Simulation:: 50,000 bits
• Noise:: Multipath Rayleigh + AWGN
Result
Table 11: BER Performance on various noise levels on different cyclic prefix
BPSK-1/2
SNR BER
1/4 1/8 1/16 1/32
1 0.0011 0 0 0
2 0 0 0 0
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5 0 0 0 0
7 0 0 0 0
10 0 0 0 0
12 0 0 0 0
15 0 0 0 0
17 0 0 0 0
20 0 0 0 0
22 0 0 0 0
25 0 0 0 0
27 0 0 0 0
30 0 0 0 0
Figure 30: BER Performance of BPSK with different CP
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Figure 31: BPSK result in term of Signal Strength and constellation diagram
Result discussion
After the iteration of simulation we are obtain the result in term of signal-strength by
which we can see that how the signal is fade after passing the channel, constellation
diagram shows that inter symbol interference.
We know that in AMC concept when the channel is more noise than the WiMAX is adapt
the lower modulation technique now the general question is arise why the system not
going with higher modulation whereas the higher modulation technique gives the
freedom of sending the more data as compare to lower modulation technique.
My dissertation result shows that why the higher modulation technique is not appropriate
for the noise channel in table we can clearly see that when SNR is too low then the BER
is nearly negligible, that’s why BPSK is useful for noise channel.
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Module-II
Parameter (QPSK- 1/2)
• Modulation scheme:: QPSK
• Source:: Random Number (randint(23*8,1); )
• R-S Coding Rate:: (32,24,4)
• Convolution Encoding:: 2/3
• Interleaving:: [1; 1; 0; 1]
• FFT Size:: 256
• Channel:: 16
• Simulation:: 50,000 bits
• Noise:: Multipath Rayleigh + AWGN
Parameter (QPSK- 3/4)
• Modulation scheme:: QPSK
• Source:: Random Number (randint(35*8,1); )
• R-S Coding Rate:: (40,36,2)
• Convolution Encoding:: 5/6
• Interleaving:: [1; 1; 0; 1; 1; 0; 0; 1; 1; 0]
• FFT Size:: 256
• Channel:: 16
• Simulation:: 50,000 bits
• Noise:: Multipath Rayleigh + AWGN
Result
Table 12: BER Performance on various noise levels on different cyclic prefix
4-QAM 1/2 4-QAM 3/4
SNR BER BER
1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32
1 0.1803 0.2428 0.2203 0.1639 0.3607 0.3545 0.3446 0.3277
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2 0.0942 0.1105 0.0797 0.0053 0.3598 0.3089 0.3607 0.3241
5 0 0 0.0018 0 0.2241 0.1982 0.2598 0.3018
7 0 0 0 0 0.0205 0.0491 0.0125 0.1018
10 0 0 0 0 0 0 0 0
12 0 0 0 0 0 0 0 0
15 0 0 0 0 0 0 0 0
17 0 0 0 0 0 0 0 0
20 0 0 0 0 0 0 0 0
22 0 0 0 0 0 0 0 0
25 0 0 0 0 0 0 0 0
27 0 0 0 0 0 0 0 0
30 0 0 0 0 0 0 0 0
Figure 32: BER Performance of QPSK(1/2) with different CP
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Figure 33: BER Performance of QPSK (5/6) with different CP
Figure 34: QPSK result in term of Signal Strength and constellation diagram
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Result discussion
In module-2 we see that 4-QAM with code rate of 1/2 have the greater capability for find
and corection the errors through R-S encoding scheme in 4-QAM with 1/2 code rate the
error correcting capability is 2t=8, where 4-QAM with code rate of 3/4 is 2t=4. So we can
see that the BER performance of 4-QAM with code rateof 1/2 is better than 4-QAM 3/4.
When the channel condition is some what good than uppar modulation technique
can be opt with choice of different code rate. The main advange with higher modulation
technique is that we can impose he ore number of bits on a same carrier cycle, so we are
gatting the higer throuhput.
Module-III
Parameter (16-QAM- 1/2)
• Modulation scheme:: 16-QAM
• Source:: Random Number (randint(47*8,1); )
• R-S Coding Rate:: (64,48,8)
• Convolution Encoding:: 2/3
• Interleaving:: [1; 1; 0; 1]
• FFT Size:: 256
• Channel:: 16
• Simulation:: 50,000 bits
• Noise:: Multipath Rayleigh + AWGN
Parameter (16-QAM- 3/4)
• Modulation scheme:: 16-QAM
• Source:: Random Number (randint(71*8,1); )
• R-S Coding Rate:: (80,72,4)
• Convolution Encoding:: 5/6
• Interleaving:: [1; 1; 0; 1; 1; 0; 0; 1; 1; 0]
• FFT Size:: 256
• Channel:: 16
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• Simulation:: 50,000 bits
• Noise:: Multipath Rayleigh + AWGN
Result
Table 13: BER Performance on various noise levels on different cyclic prefix
16-QAM 1/2 16-QAM 3/4
SNR BER BER
1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32
1 0.3236 0.3191 0.3236 0.3573 0.2500 0.2412 0.2588 0.2386
2 0.3218 0.2996 0.3050 0.3777 0.2526 0.2306 0.2518 0.2553
5 0.2846 0.3112 0.2890 0.3218 0.1136 0.2526 0.2544 0.2412
7 0.1543 0.1924 0.2004 0 0.2403 0.2500 0.2500 0.2386
10 0.0195 0.0168 0.0443 0 0.2245 0.2474 0.2482 0.2474
12 0 0 0 0 0.2280 0.2456 0.2280 0.1857
15 0 0 0 0 0 0.0449 0 0
17 0 0 0 0 0 0 0 0
20 0 0 0 0 0 0 0 0
22 0 0 0 0 0 0 0 0
25 0 0 0 0 0 0 0 0
27 0 0 0 0 0 0 0 0
30 0 0 0 0 0 0 0 0
Result discussion
In module-3 we see that 16-QAM with code rate of 1/2 have the greater capability for
find and corection the errors through R-S encoding scheme in 16-QAM with 1/2 code
rate the error correcting capability is 2t=16, where 16-QAM with code rate of 3/4 is 2t=8.
So we can see that the BER performance of 16-QAM with code rateof 1/2 is better than
16-QAM 3/4.
The question is what is need of 3/4 code rate whereas 1/2 is available which is more
efficient so the answer is when the signal is fluctuate for the less amount of nose level
then we have the choice uder the less SNR level.
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Figure 35: BER Performance of 16-QAM (1/2) with different CP
Figure 36: BER Performance of 16-QAM (1/2) with different CP
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Figure 37: 16-QAM result in term of Signal Strength and constellation diagram
Module-IV
Parameter (64-QAM- 2/3)
• Modulation scheme:: 64-QAM
• Source:: Random Number (randint(143*8,1); )
• R-S Coding Rate:: (64,48,8)
• Convolution Encoding:: 3/4
• Interleaving:: [1; 1; 0; 1; 1; 0]
• FFT Size:: 256
• Channel:: 16
• Simulation:: 50,000 bits
• Noise:: Multipath Rayleigh + AWGN
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Parameter (64-QAM- 3/4)
• Modulation scheme:: 64-QAM
• Source:: Random Number (randint(143*8,1); )
• R-S Coding Rate:: (80,72,4)
• Convolution Encoding:: 5/6
• Interleaving:: [1; 1; 0; 1; 1; 0; 0; 1; 1; 0]
• FFT Size:: 256
• Channel:: 16
• Simulation:: 50,000 bits
• Noise:: Multipath Rayleigh + AWGN
Result
Table 14: BER Performance on various noise levels on different cyclic prefix
64-QAM 2/3 64-QAM 3/4
SNR BER BER
1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32
1 0.2625 0.2539 0.2388 0.2336 0.2625 0.2582 0.2436 0.2465
2 0.0277 0.2632 0.2440 0.2421 0.0277 0.2564 0.2360 0.2447
5 0.2461 0.2467 0.2513 0.2566 0.2461 0.2523 0.2588 0.2523
7 0.2408 0.2395 0.2539 0.2612 0.2408 0.2395 0.2471 0.2512
10 0.2230 0.2184 0.2316 0.2507 0.2230 0.2436 0.2377 0.2582
12 0.2329 0.2157 0.1941 0.2349 0.2329 0.2325 0.2360 0.2782
15 0.1678 0.1704 0.1625 0.1829 0.1678 0.2284 0.2319 0.2658
17 0.0500 0.0631 0.0493 0.1211 0.0500 0.2412 0.2068 0.2389
20 0.0450 0.0638 0 0 0.0450 0.2202 0.1530 0.2348
22 0 0 0 0 0 0.1343 0.0625 0.2179
25 0 0 0 0 0 0.0608 0 0
27 0 0 0 0 0 0 0 0
30 0 0 0 0 0 0 0 0
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Result discussion
In last module we can see that when the SNR is high then we get the perfect
communication, on the other hand we can see that the BER is also depending on the FEC
scheme when the error correcting coding is more efficient then the BER is minimum.
The result shows that the higher rate (when more bits are sending on same time of
interval) is only possible when the channel condition is good as we are saying in AMC.
So it is clear that there is a tradeoff between the throughput and BER on the constant
SNR.
Figure 38: BER Performance of 64-QAM (2/3) with different CP
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Figure 39: BER Performance of 64-QAM (3/4) with different CP
Figure 40: 64-QAM result in term of Signal Strength and constellation diagram
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7.2 Probability of Symbol Error
Probability of Error (Pe) is important to find out the error rate in a system because it
affects fading and noise in a channel at transmitting and receiving end. From the
following formula Probability of Error for M-array PSK has been calculated.
From the following formula Probability of Error for M-array PSK has been calculated.
(16)
Probability of Error for M-array QAM has been calculated through this formula which is
as follows,
(17)
Where:
erfc= error function
M=M-array Modulation
Es= Energy per symbol (Joules)
N0=Noise Power Spectral density
Due to fading and Doppler shift effect, the Probability of Error of the system increased
resulting the physical layer performance degrades. At this circumstance, we used channel
model as a Rayleigh distribution which is mentioned in chapter one. We presented the
different error probability in figure for all adaptive modulation schemes. In this section
we have shown the probability of error for all mandatory modulations with AWGN.
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Figure 41: Probability of symbol error for the different transmitted power
7.3 Analysis
After getting the result of two modules under the AMC, we have to find that there is a
tradeoff between BER and Modulation Scheme, i.e. when the channel condition is good
then the system can opt the higher modulation scheme so that we can impose the more
data without losing the bits but while we are opt the higher modulation scheme on the
poor channel condition then we should deal with higher BER.
So the result shows that the lower modulation scheme is give the higher efficiency
on the poor channel condition.
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Chapter Eight
“Conclusion & Future Work”
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8.1 Conclusion
In this dissertation we have prepared a simulation model of the physical layer of IEEE
802.16e. The performance is measure for different modulation technique with different
coding rate in terms of BER. We know that fading is one of the main aspects of wireless
communication. At the starting of our simulation, we used AWGN channel and got same
results using Rayleigh fading and AWGN. After obtaining the result it was found that
with the same channel condition the lower modulation technique gives the lower BER
and lower transmission efficiency where higher modulation technique like 16-QAM give
higher BER with better transmission efficiency. This model is very useful for analysis the
effect of different modulation technique, and also this model helps to optimize the overall
system.
And also by getting the probability of symbol error (Pe) we see that at lower power the
probability of occurring the error is low for a constant bandwidth and at ambient
temperature.
8.2 Limitation of Work In our dissertation we are obtain the result in term of BER and probability of error, we are
trying to add the MAC layer component like scheduling, radio resource allocation and
security but our simulator does not provide the freedom to include of them.
8.3 Future Work In future we try to include MIMO and Higher modulation technique (like 64-qam and
128-qam) in the system and also trying to introduce the MAC layer functionality to
provide the QoS for the classified traffic.
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Appendix A MATLAB CODE FOR WiMAX SIMULINK SCENARIO clear clc BW=input('Required channel bandwidth in MHz(max 20 MHz)= '); disp('choose cyclic prefix to overcome delays spreads') disp('1/4 for longest delay spread ,') disp('1/8 for long delay spreads ,') disp('1/16 for short delays spreads ,') disp('1/32 for very small delay spread channels') G=input('= '); channels=[1.75 1.5 1.25 2.75 2.0]; oversampling=[8/7 86/75 144/125 316/275 57/50 8/7]; for i=1:5 y(i)=rem(BW,channels(i)); if y(i)==0 n=oversampling(i); end end y=(y(1))*(y(2))*(y(3))*(y(4))*(y(5)); if y~=0 n=8/7; end if ((G~=1/4)&(G~=1/8)&(G~=1/16)&(G~=1/32)) error('u have choosed a guard period thats not valid in the ieee 802.16') end Nused=200; Nfft=256; fs=(floor((n*BW*1e6)/8000))*8000; %sampling freqency freqspacing= fs/Nfft; %freqency spacing Tb= 1/freqspacing; %usfel symbol time Tg= G*Tb ;%Guard time Ts=Tb+Tg ;%symbol time samplingttime= Tb/Nfft; %adaptive encoding and decoding depending on the channel SNR genpoly=gf(1,8); for idx=0:15 genpoly=conv(genpoly,[1 gf(2,8)^idx]);
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end primepoly=[1 0 0 0 1 1 1 0 1]; convvec=poly2trellis(7,[171,133]); cSNR=input('Enter the channel SNR in dB(it should be above 1 dB)= '); if cSNR<1 error('not a valid channel for transmission ,use another channel with better SNR') end %BPSK 1/2 if (1<=cSNR&cSNR<9.4) inputsize=88; seqafterrand=inputsize+8; shortening=[1:12]; shorteningRx=[1:11]; punvec=reshape([1 , 1],2,1);%convolutional of rate 1/2 Ncbps=192;%selctor of RS 12*8 k=0:Ncbps-1; mk=(Ncbps/12 )*mod(k,12)+floor(k/12); s=ceil(Ncbps/2); jk=s*floor(mk/s)+mod(mk+Ncbps-floor(12*mk/Ncbps),s); [x,int_idx]=sort(jk); Ry=[+1 -1]; Iy=[0 0]; qamconst=complex(Ry,Iy); qamconst=qamconst(:); bitspersymbol=1; CPsel=[(256-G*256+1):256 1:256]; CPremove=[(256*G+1):(256+G*256)]; coderate=1/2; disp('Modulation scheme is chosed for that particular SNR is BPSK with Coding rate 1/2'); elseif (9.4<=cSNR&cSNR<11.2) inputsize=184; seqafterrand=inputsize+8; shortening=[1:32]; shorteningRx=[1:23]; punvec=reshape([1 0 , 1 1],4,1);%convolutional of rate 2/3 Ncbps=384; %selctor of RS 48*8 k=0:Ncbps-1; mk=(Ncbps/12 )*mod(k,12)+floor(k/12); s=ceil(Ncbps/2);
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jk=s*floor(mk/s)+mod(mk+Ncbps-floor(12*mk/Ncbps),s); [x,int_idx]=sort(jk); Ry=ones(2,1)*[+1 -1]; Iy=([+1 -1]')*ones(1,2); qamconst=complex(Ry,Iy); qamconst=qamconst(:)/sqrt(2); bitspersymbol=2; CPsel=[(256-G*256+1):256 1:256]; CPremove=[(256*G+1):(256+G*256)]; coderate=1/2; disp('Modulation scheme is chosed for that particular SNR is QPSK with Coding rate 1/2'); elseif (11.2<=cSNR&cSNR<16.4) inputsize=280; seqafterrand=inputsize+8; shortening=[1:40]; shorteningRx=[1:35]; punvec=reshape([1 0 1 0 1, 1 1 0 1 0],10,1);%convolutional of rate 5/6 Ncbps=384; %selctor of RS 48*8 k=0:Ncbps-1; mk=(Ncbps/12 )*mod(k,12)+floor(k/12); s=ceil(Ncbps/2); jk=s*floor(mk/s)+mod(mk+Ncbps-floor(12*mk/Ncbps),s); [x,int_idx]=sort(jk); Ry=ones(2,1)*[+1 -1]; Iy=([+1 -1]')*ones(1,2); qamconst=complex(Ry,Iy); qamconst=qamconst(:)/sqrt(2); bitspersymbol=2; CPsel=[(256-G*256+1):256 1:256]; CPremove=[(256*G+1):(256+G*256)]; coderate=3/4; disp('Modulation scheme is chosed for that particular SNR is QPSK with Coding rate 3/4'); elseif (16.4<=cSNR&cSNR<18.2) inputsize=376; seqafterrand=inputsize+8; shortening=[1:64]; shorteningRx=[1:47]; punvec=reshape([1 0 , 1 1],4,1);%convolutional of rate 2/3
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Ncbps=768; %selctor of RS 96*8 k=0:Ncbps-1; mk=(Ncbps/12 )*mod(k,12)+floor(k/12); s=ceil(Ncbps/2); jk=s*floor(mk/s)+mod(mk+Ncbps-floor(12*mk/Ncbps),s); [x,int_idx]=sort(jk); Ry=ones(4,1)*[+1 +3 -1 -3]; Iy=([+1 +3 -3 -1]')*ones(1,4); qamconst=complex(Ry,Iy); qamconst=qamconst(:)/sqrt(5); bitspersymbol=4; CPsel=[(256-G*256+1):256 1:256]; CPremove=[(256*G+1):(256+G*256)]; coderate= 1/2; disp('Modulation scheme is chosed for that particular SNR is 16-QAM with Coding rate 1/2'); elseif (18.2<=cSNR&cSNR<22.7) inputsize=568; seqafterrand=inputsize+8; shortening=[1:80]; shorteningRx=[1:71]; punvec=reshape([1 0 1 0 1, 1 1 0 1 0],10,1);%convolutional of rate 5/6 Ncbps=768; %selctor of RS 96*8 k=0:Ncbps-1; mk=(Ncbps/12 )*mod(k,12)+floor(k/12); s=ceil(Ncbps/2); jk=s*floor(mk/s)+mod(mk+Ncbps-floor(12*mk/Ncbps),s); [x,int_idx]=sort(jk); Ry=ones(4,1)*[+1 +3 -1 -3]; Iy=([+1 +3 -3 -1]')*ones(1,4); qamconst=complex(Ry,Iy); qamconst=qamconst(:)/sqrt(5); bitspersymbol=4; CPsel=[(256-G*256+1):256 1:256]; CPremove=[(256*G+1):(256+G*256)]; coderate= 3/4; disp('Modulation scheme is chosed for that particular SNR is 16-QAM with Coding rate 3/4'); elseif (22.7<=cSNR&cSNR<24.4) inputsize=760;
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seqafterrand=inputsize+8; shortening=[1:108]; shorteningRx=[1:95]; punvec=reshape([1 0 1 , 1 1 0 ],6,1);%convolutional of rate3/4 Ncbps=1152; %selctor of RS 144*8 k=0:Ncbps-1; mk=(Ncbps/12 )*mod(k,12)+floor(k/12); s=ceil(Ncbps/2); jk=s*floor(mk/s)+mod(mk+Ncbps-floor(12*mk/Ncbps),s); [x,int_idx]=sort(jk); Ry=ones(8,1)*[+3 +1 +5 +7 -3 -1 -5 -7 ]; Iy=([+3 +1 +5 +7 -3 -1 -5 -7 ]')*ones(1,8); qamconst=complex(Ry,Iy); qamconst=qamconst(:)/sqrt(21); bitspersymbol=6; CPsel=[(256-G*256+1):256 1:256]; CPremove=[(256*G+1):(256+G*256)]; coderate= 2/3; disp('Modulation scheme is chosed for that particular SNR is 64-QAM with Coding rate 2/3'); elseif 24.4<=cSNR inputsize=856; seqafterrand=inputsize+8; shortening=[1:120]; shorteningRx=[1:107]; punvec=reshape([1 0 1 0 1, 1 1 0 1 0],10,1);%convolutional of rate 5/6 Ncbps=1152; %selctor of RS 144*8 k=0:Ncbps-1; mk=(Ncbps/12 )*mod(k,12)+floor(k/12); s=ceil(Ncbps/2); jk=s*floor(mk/s)+mod(mk+Ncbps-floor(12*mk/Ncbps),s); [x,int_idx]=sort(jk); Ry=ones(8,1)*[+3 +1 +5 +7 -3 -1 -5 -7 ]; Iy=([+3 +1 +5 +7 -3 -1 -5 -7 ]')*ones(1,8); qamconst=complex(Ry,Iy); qamconst=qamconst(:)/sqrt(21); bitspersymbol=6; CPsel=[(256-G*256+1):256 1:256]; CPremove=[(256*G+1):(256+G*256)]; coderate= 3/4;
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disp('Modulation scheme is chosed for that particular SNR is 64-QAM with Coding rate 3/4'); end
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Appendix B MATLAB CODE FOR PROBABILITY OF SYMBOL ERROR (PE) FOR AWGN CHANNEL
clc; clear; BW=input('enter channel bandwidth in MHz(max 20 MHz)= '); TP=input('enter the transmitted power(in mW)= '); M=input('select M-arry modulation= '); No=-174; %No=KT(K=Boltzman’s constant ant T=Ambient temperature =290K) Et=(TP/BW)*(10^-6); dbm =10*log10(Et); Es=dbm-120; %where -120dB is channel attenuation SNR=Es+174; Eb_by_No=SNR-(10*log10(M)); Pe=(2*(1-(1/sqrt(M))))*erfc(sqrt(3*Es/(2*(M-1)*No)));